Key Takeaways

• Plan strategically by balancing high-value learning sessions and targeted expo floor demos to avoid overload.
• Focus on one anchor theme each day to dive deeper into specific topics like GenAI or MLOps.
• Create a shortlist of 8-10 booths to prioritize during the expo floor sprint for efficient demos.
• Visit the Start-Up Area to spot emerging trends and solutions in AI tooling and collect ideas.
• Visit the D-ID Booth to learn more about our AI Avatars and Agents

If you’re heading to the AI & Big Data Expo in London, you’re about to get hit with a lot (in a good way): big-name enterprise speakers, hands-on demos, startup energy, and seven co-located events under one roof. It’s one of those events where you can either leave feeling energized and informed… or leave with sore feet and a head full of half-remembered acronyms. It’s two days at Olympia London (Feb 4–5, 2026), and it’s easy to either over-pack your schedule… or wander around and accidentally miss the best stuff.

Below are seven simple, high-impact moves to make the most of it.

1. Build a “two-lane” agenda: one lane for learning, one lane for demos

The fastest way to have a good conference is to split your time intentionally:

• Lane A: sessions that sharpen your POV (strategy, real deployments, hard lessons)
• Lane B: expo-floor demos that show what’s actually usable right now

Quick move: choose 2–3 sessions you must catch each day. Everything else becomes optional.

2. Pick one anchor theme per day (so you don’t end up doing nothing deeply)

This event is big, and the real value comes from going deeper in one area rather than sampling 30 things. Pick a theme you care about (GenAI, MLOps, governance, data infrastructure, AI in specific industries) and let that guide your choices.

3. Do an “expo-floor sprint” with a shortlist

Wandering is fun for 20 minutes — then it becomes chaos.

Make a shortlist of 8–10 booths you want to hit, and keep your demos short and focused.

Two questions that cut through fluff:

1. “What does this replace or simplify?”
2. “What does production look like in 30 days?”

4. Visit D-ID’s booth (and ask for a demo that matches your use case) 

If you want a quick, tangible glimpse of where AI communication is going, go see D-ID at our booth (187).

Make it worth it: ask Steve and Fred to show you how AI avatars and visual agents can turn explainers, onboarding, training, and customer interactions into a more human, face-to-face experience.

5. Hop into one co-located event that solves your biggest bottleneck

AI projects don’t fail because the model didn’t exist. They fail because security, data plumbing, deployment, or automation wasn’t ready. The co-located tracks make it easy to plug that gap while you’re already there. 

6. Spend real time in the Start-Up Area

Even if you’re enterprise-focused, the Start-Up zone is where you’ll spot the next wave of product patterns early. You’re basically getting a “what’s coming next” radar sweep.

Quick move: use your time to collect ideas, not swag. pay attention to the recurring problems startups keep trying to solve.

7. After hours: what to do around Olympia (when your brain is full)

Olympia is in a great pocket of London for a post-conference reset. A few easy options:

• Kensington High Street: an easy walk, lots of places to grab food, low-effort wandering.
• Holland Park: if you want greenery and quiet to decompress.
• Notting Hill / Portobello Road: if you feel like exploring and turning the evening into a mini-London moment.
• Classic pub evening nearby: perfect for informal “okay, what did you actually think?” debriefs with your team.

As AI & Big Data Expo Global London gets closer, it’s worth going in with a simple game plan so you can actually make the most of it. Between the big-picture sessions, hands-on demos, and plenty of chances to meet the people building what’s next, this is one event you won’t want to skim. And of course, swing by D-ID’s booth (187) to say hi and get a live look at our latest in expressive avatars and visual agents. For the full agenda and logistics, head to the event site. See you in London!

FAQs

The post 7 Things You Don’t Want to Miss at AI & Big Data Expo London appeared first on D-ID.

New York, NY — December 10, 2025 — The Scott-Morgan Foundation, in collaboration with

D-ID, today announced the launch of SMF VoXAI, a multi-agentic AI-powered platform that restores the natural flow of conversation for people with severe communication disabilities.

The launch marks the culmination of a five-year global experiment in ethical, human-centred AI led by the Scott-Morgan Foundation CEO LaVonne Roberts. The initiative unites disability advocates, universities, and a consortium of NVIDIA Inception AI companies, including D-ID, ElevenLabs, and Irisbond, alongside NVIDIA infrastructure and Lenovo, the global technology leader, whose partnership realizes founder Dr. Peter Scott-Morgan’s vision that every device should include accessibility as standard. Students at partner Tecnológico de Monterrey each dedicated over 400 hours to developing and testing SMF VoXAI and conducting the first empirical research on how expressive avatars enhance communication.

SMF VoXAI was developed by the Foundation’s Chief Technologist, Bernard Muller, who is fully paralyzed by ALS and architected the entire system using only eye-tracking technology. The platform embodies the Foundation’s principle of ‘designing with, not for.’

“Two years ago, this would have been impossible,” says Scott-Morgan Foundation CEO LaVonne Roberts. “Today, a technologist who’s lived with ALS for 15 years and mastered coding through eye-tracking alone has designed AI coordination that restores agency instead of replacing it, proving that when you design WITH the people who need solutions most, you build what Big Tech couldn’t. This gives people back what they’ve been locked out of: their own voices, their presence, their lives.”

The platform was presented publicly for the first time on December 10th at the AI Summit New York, during the live session “Against Silence: How Extreme Constraint Built the Most Sophisticated Ambient AI in Production.”

Powered by D-ID’s Real-Time Streaming API and advanced agentic AI capabilities, SMF VoXAI brings conversation to life through photorealistic, responsive digital avatars that convey users’ words and emotions in real time. The ultra-low-latency system, driven by NVIDIA GPUs and incorporating voice and eye-gaze solutions by ElevenLabs and Irisbond, enables people who communicate via eye-tracking technology to engage in natural, face-to-face dialogue, turning delayed text into immediate presence and transforming passive interaction into dynamic human connection.

Globally, more than 100 million people live with conditions that severely limit speech, including Amyotrophic Lateral Sclerosis (ALS), which affects over 340,000 people worldwide, as well as those recovering from stroke, living with cerebral palsy, traumatic brain injury, or non-verbal autism (WHO Foundation).  SMF VoXAI is the first ambient AI communication system designed entirely by someone who depends on it. For many, even a short delay in communication can lead to isolation and emotional distress. SMF VoXAI helps close that gap, restoring not just speech, but the ability to participate fully in life’s most human moments. Unlike traditional AAC devices costing $10,000-$15,000, the Foundation offers SMF VoXAI through a freemium model—free basic access worldwide, and $30/month for premium features—making this technology accessible to everyone who needs it.

“This realizes what we learned supporting Stephen Hawking and Dr. Peter Scott-Morgan that technology should restore presence, not just provide function,” said Thorsten Stremlau, Foundation CTO and NVIDIA Distinguished Engineer. “With D-ID’s real-time video generation, users don’t just speak, they’re seen and felt in the moment. This realizes Peter’s vision: technology that keeps people in their own lives, not watching from the sidelines.”

“SMF VoXAI represents the next evolution of human-machine collaboration,” said Gil Perry, CEO and Co-Founder of D-ID. “By combining the empathy of human expression with the autonomy of agentic AI, we’re making communication accessible, natural, and emotionally intelligent for everyone, no matter their physical limitations.”

“D-ID’s avatars don’t just make me visible, they make me present,” said Bernard Muller, who architected SMF VoXAI using only eye-tracking technology. “When someone sees my avatar smile or shows concern, they’re seeing me, not a disability. That changes everything about how I connect with my world.”

Experience SMF VoXAI at the demonstration booth at the AI Summit New York, Dec. 10th, 11th:

• SMF VoXAI, the real-time dialogue engine enabling spontaneous, responsive participation.


• D-ID’s streaming avatars, the visual layer that gives every interaction a human face reflecting emotion and identity.

Global Research & Pilot Program

The Scott-Morgan Foundation and D-ID announced a two-year research collaboration tracking 20 participants across six countries. Led by Dr. Antonio Ortiz at Tecnológico de Monterrey, the research provides the first empirical evidence of how D-ID’s expressive avatars and ElevenLabs’ voice clones restore identity and improve communication quality, measuring not just speed, but emotional presence and participation outcomes. The accompanying two-year study across six countries will generate the first empirical data on how AI avatars affect quality of life for people with communication disabilities.

About the Scott-Morgan Foundation: The Scott-Morgan Foundation is a UK-based charity dedicated to transforming the lives of people with extreme disabilities through advanced technology, research, and advocacy. Its mission is to ensure that cutting-edge innovation serves the most vulnerable communities, empowering people to live and love without limits. https://www.scottmorganfoundation.org

About D-ID: D-ID is the world leader in generative AI for video and digital humans, enabling frictionless, real-time interaction through its Real-Time Streaming API. Its technology powers lifelike digital presenters, learning companions, and virtual assistants for Fortune 500 companies and mission-driven organizations alike. In September 2025, D-ID acquired simpleshow, the global pioneer in AI-based explainer video creation. Based in Berlin, simpleshow helps organizations in more than 70 countries simplify complex messages through smart, scalable, and human-centric video communication. Simpleshow, a D-ID Company. https://www.d-id.com

PRESS CONTACT:
Leah Stern, D-ID Press Office: press@d-id.com  / +44 747 019 6826

The post Press Release: Scott-Morgan Foundation and D-ID Introduce SMF VoXAI appeared first on D-ID.

The next big shift is already underway, transitioning from static chatbots and one-way interfaces to intelligent, human-like visual AI agents that can see, speak, and respond in real time.

These agents combine the intelligence of large language models with the expressiveness of digital avatars, creating experiences that feel less like typing into a machine and more like talking to a real person. They can guide new employees through onboarding, deliver consistent customer support around the clock, or even represent a brand in live, interactive video conversations.

Unlike text-only tools, these multimodal systems bring communication to life through visual presence, tone, and emotion. The result is a new kind of interaction, an experience that’s not only efficient, but also personal, memorable, and distinctly human.

What Are Visual AI Agents and How Do They Work?

Visual AI agents are multimodal, goal-based AI systems designed to interact through both visual and conversational channels. In simple terms, they don’t just respond, they communicate.

They combine several advanced technologies:

• Large Language Models (LLMs) to understand intent and generate natural responses
  
• Video rendering to power realistic, expressive avatars
  
• Real-time vision models to interpret gestures, visuals, or screens
  
• Retrieval-Augmented Generation (RAG) to access secure enterprise data in real time
  

Together, these systems allow enterprises to build visual AI agents that not only hold a conversation but truly assist, capable of guiding users through workflows, explaining processes, and creating meaningful connections.

For a deeper look at how AI agents differ from avatars, see AI Agents vs. AI Avatars.

Why Enterprises Are Embracing Visual AI Agents

The move toward enterprise AI agents represents a fundamental evolution in digital experience design.

Here’s why leading organizations are making the switch:

1. From Static to Interactive

Traditional chatbots are limited to text-based exchanges. Visual AI agents bring communication to life by combining conversation with facial expressions, gestures, and tone, resulting in interactions that feel more personal and engaging.

2. Scalability Meets Personalization

Visual AI agents can serve thousands of users simultaneously, yet tailor each and every conversation based on language, sentiment, or behavioral cues. This balance between scale and empathy is why enterprises use them across global operations.

3. Always-On, Multilingual, and Consistent

Unlike human representatives, visual agents don’t sleep. They can engage customers or employees around the clock, in multiple languages, with perfect consistency, reducing operational costs while improving user experience.

4. Improved Training and Onboarding

Organizations can deploy agents as virtual trainers or HR assistants. Employees learn faster when information is presented by a relatable, face-to-face digital guide rather than static materials.

5. Enhanced Brand Connection

The use of branded, photorealistic avatars helps companies create a unified identity across platforms — websites, LMS systems, intranets, or customer portals — reinforcing trust and recognition.

Key Use Cases of Visual AI Agents in Enterprise Environments

Visual AI agents are already proving their value across departments, enhancing efficiency, improving user experience, and creating a more human touch across digital channels. Here are some of the most common and impactful use cases:

Customer Support

Visual AI agents can instantly greet customers, answer common questions, and guide them step-by-step through troubleshooting or onboarding processes. Unlike static chatbots, they respond with empathy, tone, and facial expression, creating a sense of genuine assistance. Companies can deploy these agents directly on their websites or support portals to reduce wait times, deliver consistent answers, and operate 24/7 and in any language.

Employee Onboarding

For HR and Learning & Development teams, visual AI agents act as friendly digital trainers.
They introduce company culture, walk new hires through policies and workflows, and provide answers in real time.  This reduces the pressure on HR teams and ensures that every employee receives a consistent, engaging introduction to the organization, even in distributed or hybrid workplaces.

Sales Enablement

In sales and marketing, visual AI agents serve as dynamic product presenters.
They can deliver tailored demos, explain features or pricing, and follow up with leads automatically. By adding a human face and voice, these agents create stronger engagement than static videos or PDFs, helping sales teams reach more prospects with less manual effort.

Compliance and Policy Training

Enterprises often struggle to make compliance content engaging.
Visual AI agents turn complex regulations and internal policies into short, easy-to-follow explainers, personalized to each employee’s role or region.They ensure that updates are understood and retained, while tracking engagement metrics to prove completion and compliance.

Corporate Communication

Leadership communication can often feel distant, especially in large organizations.
With visual AI agents, executives can share company updates, celebrate milestones, or announce new initiatives in a more personal, face-to-face way. Branded avatars can reflect the company’s tone and style, helping messages feel authentic and unified across teams and regions.

It’s clear that AI agents for enterprise are no longer just automation tools. They represent a new layer of digital connection that bridges the gap between efficiency and empathy in the modern workplace.

For more insights on the rise of intelligent agents, explore our post Top AI Agents in Business Use Cases

Best Practices for Building a Visual AI Agent for Your Organization

Creating a successful visual AI agent requires more than simply selecting an avatar. It’s a strategic process that blends technology, psychology, and user experience.

1. Define the Agent’s Goal

Every effective agent starts with a clear purpose — whether it’s onboarding new hires, delivering training, or assisting customers. Define measurable goals early to shape the model’s responses and behavior.

2. Train with High-Quality Data

Data quality defines the agent’s performance. Combine company-specific knowledge bases, FAQs, and policy documents with LLM fine-tuning or AI agent training techniques for consistent, brand-aligned responses.
Learn more in our glossary entry on AI Agent Training.

3. Choose the Right Avatar and Personality

Visual design impacts trust and engagement. Pick an avatar that reflects your brand tone — friendly, professional, or expert — and ensure consistent facial expressions and voice delivery.

4. Integrate Seamlessly with Existing Systems

Visual AI agents work best when connected to your enterprise stack. Use APIs to link them to CRM, LMS, or HR tools, enabling real-time data flow and automated responses.

5. Ensure Security and Compliance

For enterprises, governance is key. Choose platforms that encrypt communication, log conversations, and comply with standards like GDPR or SOC 2.

For guidance on tools that simplify this process, check our overview of Best AI Agent Tools.

Next Steps: Bring Human Connection to Your Enterprise AI

Visual AI agents combine intelligence with empathy and that’s what makes them so powerful. They can explain, support, and connect in ways that text alone never could.

If your organization is ready to reimagine communication, start by identifying where human-like interaction can make the biggest difference. Is it in onboarding, customer engagement, or training? Once you know the “why,” the “how” becomes simple.

Ready to explore? Contact us or sign up to start building your first visual AI agent today.

The post Enterprise Benefits of Deploying Visual AI Agents appeared first on D-ID.

We all know that to stay competitive, your people have to be at the top of their game. And that’s where learning and development programs play a critical role. Workplace skills require constant updating, which in turn means corporate L&D must easily and quickly adapt to individual employee training needs. Where many companies get lost is in managing this gargantuan effort: and that’s where generative AI in learning and development tools, such as D-ID’s video generation and interactive avatar creation, step in to save the day.

Challenges in Corporate Training

If the “global skills gap” isn’t affecting your company yet, it likely will in the near future. This term refers to the widespread need for businesses to continually adapt to changes in workplace skills, driven in part by advancements in AI and increased digitization. In light of this trend, nearly half of all employees will need to be retrained in the next 10 years, according to the Society for Human Resources Management, highlighting the growing importance of Generative AI in Learning and Development as a scalable solution.

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The response to this near-crisis has been a huge investment in corporate learning and development budgets. Today, the global corporate L&D market is worth $340 billion, which translates to more than $1,500 spent on an average employee this year alone.  

Value for Money

For HR departments, the question is about spending this funding wisely. The learning and development needs of numerous employees can result in hundreds of courses that need frequent updates to keep up with the constantly evolving skill demands. At the same time, L&D programs must be interesting and present the material in ways that lead to easy skill adoption and proper use.

Personalization and Capacity

A Harvard survey found that only 12% of employees use the skills they acquire in L&D programs in their jobs. A major reason for this failure is scale. Each employee has different learning needs that are affected by their role, personal abilities, and the future strategy of the company. Plus, each worker has his or her preferences for learning style and scheduling. Added to this challenge is the fact that L&D content must be engaging, memorable, and relevant in order to be effective. Many small organizations simply don’t have the resource capacity to create L&D programs that answer such needs. 

Quality and Effectiveness

When a company provides employees with training materials, they need to be uniform and consistent so that everyone approaches their job in the correct manner. This is particularly crucial in interpersonal interactions, ensuring that employees adhere to company standards in a way that is universally understood.

For instance, in customer service roles, employees should be adept at handling typical customer inquiries, and their responses should align with the company’s branding. Dealing with sophisticated business clients requires different skills than helping mid-range consumers. The key to getting this complex situation right is an easily customizable training program and a proper onboarding process.

Solutions Offered by Generative AI

One of the primary reasons employees are undergoing retraining is artificial intelligence – but Generative AI in Learning and Development is also the answer to many of these challenges.

Generative AI produces an enormous array of content, including text, pictures, audio, and synthetic data. Popular Gen AI platforms include ChatGPT, Claude, and Gemini. When it comes to learning and development, organizations can leverage Gen AI capabilities, such as:

General Content Creation Tools

With minimal user guidance, AI platforms can generate text, presentations, and images and then combine these elements to create complete courses. Organizations can integrate Gen AI output with a Learning Management System (LMS) as the physical platform through which to deliver content. 

It all starts with the analysis of massive datasets. AI combs through thousands of hours of instruction, and millions of records of learner interactions, to automatically create up-to-date L&D material that can be adjusted to individual employees. The appearance and user experience of online courses can be modified by providing specific instructions to the Gen AI platform, often based on feedback from employees.

When it comes to student evaluations, Gen AI can analyze existing course tests and adapt them for an organization’s use. With the right prompts and a combination of AI and LMS technologies, quizzes, micro-content, interactive learning programs, visual instruction, and gamification are all possible.

Image and Video-Based Avatars

The next step up from a multimedia learning environment is the utilization of static and dynamic video avatars. The advantages of video avatars are clear: 

• It is much more engaging to look at a human face than it is to read diagrams or text.
• Learning from an actual person is how most of us were taught in school.
• Videos are more eye-catching and relatable. 

Yet the same is true even for static images. Observing an image of an individual associated with the subject matter being studied provides a vital “power of presence” that is important for us as social beings. This is one of the reasons why ads that show a person’s face attract much more attention than other types of images. Looking at someone’s face also delivers an important message in terms of expression and helps the learner to humanize the story, which makes the instruction more memorable.    

Interactive Visual Agents

Perhaps the most innovative form of Gen AI-powered L&D is the interactive D-ID Visual Agents technology. It delivers all the speed and effectiveness of AI content creation but with a human-like avatar that can answer questions and provide skills training. Customizing Visual Agents is as simple as choosing its physical appearance and voice. The knowledge used by the Visual Agent in its interactions is based on your own source material, which is then leveraged by retrieval augmented generation (RAG) technology to deliver accurate answers to queries. When a user has a question for their Visual Agent, they simply type it or speak with their microphone. Speaking with interactive Visual Agents is made even more realistic by their rapid response rate, allowing the interaction to feel like a real conversation. The processing ability of Visual Agents technology allows an accuracy rate above 90%.

Use Cases in Learning and Development

Many organizations are already using Generative AI technology to produce learning and development courses. We’ve shared below a few standout examples of its real-world applications:

Personalized Training Modules

The School of Optometry and Vision Sciences at Bar-Ilan University partnered with D-ID to produce dozens of interactive video avatars simulating medical situations. These situations can involve a wide variety of populations, clinical issues, and even personalities. With D-ID, the School of Optometry supplies the students with content that is customized according to a large number of variables so that they can gain experience in dealing with them. One of the most valuable parts of the program is that it uses “face-to-face” conversations with an AI-based character to create a lifelike clinical setting.

Compliance Training

One of the greatest concerns of a medical institution like the School of Optometry is compliance. In the medical profession, regulations such as HIPAA in the US, or GDPR in the EU, must be followed by all relevant employees. In the wider world, there are other kinds of compliance related to financial records, personal privacy, and similar issues. And training employees to understand the complexities of these rules can be a real challenge. Companies that use AI-generated videos for compliance training ensure that it is consistent, engaging, and easily understandable across all departments.

Onboarding Processes

Onboarding is an equally crucial type of training for organizational success. At the Diplomat Group, for example, both initial and advanced training for employees is vital. By partnering with D-ID, Diplomat can now produce a wide range of video content assets, including: 

• Training videos for new systems and processes
• Instructional guides divided into a convenient module format
• A huge selection of content featuring different languages, interesting stories, and practical simulations

Interactive Avatars

One aspect of D-ID technology that especially interested Diplomat was the use of interactive avatars for corporate training. As seen with the School of Optometry, these avatars are much more than informative training tools. They enable simulations and real-time interactions with learners, which makes the L&D process more effective. Diplomat built Excel templates with sets of questions and answers which were then used to test employees on how to act in certain situations. Based on a sort of “decision tree” concept, the next question asked by the avatar is based on the user’s answer. This creates a dynamic customization process that adjusts to the user’s expertise on the fly. 

Skill Development

As an expert in the e-Learning industry, Skilldora was looking for a platform to complement its mission of leveraging artificial intelligence to expand its line of “AI Instructed Courses.” Through D-ID technology, Skilldora was able to support continuous learning and development programs that rapidly adapt according to changes in workplace skills, among other areas of activity.
Skilldora used only AI instructors to deliver content, a low-cost strategy meant to solve numerous challenges in the online L&D industry, such as:

• High course drop-out rates and associated refund costs 
• Outdated virtual L&D platforms 
• The lack of consistency regarding material and user experience due to a variety of 
course creators 

Remote Learning

Skilldora also liked D-ID’s tools for creating interactive and engaging remote learning experiences (including in virtual environments). With the growth of the hybrid work culture, it’s essential for organizations to expand their L&D capabilities beyond in-person corporate training. This is particularly important for Skilldora as its goal was to be the US leader in AI-based instruction for the online learning industry. With D-ID, Skilldora could quickly, cheaply, and easily build courses for the modern student, characterized by advanced functionality that can only be delivered with a digital solution. In addition, Skilldora sells modular courses, and so it needed a content creation technology that allows clients to purchase personalized L&D videos according to various subjects. D-ID allows organizations to build courses of any length and on any topic simply by choosing an avatar and uploading content. 

Learn More About Gen AI Learning

Staying competitive means upgrading workplace skills through modern L&D technologies. Organizations adopting Generative AI in Learning and Development are already seeing faster upskilling, higher engagement, and measurable ROI. We invite you to contact D-ID today for a consultation or visit our website for more information.

The post How Generative AI Is Transforming Corporate Learning and Development appeared first on D-ID.

This guide is here to help you cut through the noise by giving you a clear picture of the landscape and your options. While many tools offer some form of AI-driven avatar or video generation, only a select few deliver truly interactive, real-time experiences suitable for enterprise customer engagement. These are the platforms worth taking a closer look at. We’ll break down the different types of avatar tools on the market, compare some of the top players, and show you what to look for if you’re serious about transforming customer experience at an enterprise level.

Key Terms

Avatar

An avatar is a lifelike digital persona, usually a human face or full-body figure, that is animated by AI to speak, emote, and convey information on screen. Modern platforms let enterprises spin up thousands of such avatars for marketing, training, or customer support content at scale.

AI Agent
An autonomous software entity that senses its environment, reasons with machine-learning models or symbolic rules, and takes actions toward a goal. In practice, an AI Agent might schedule meetings, optimize supply chains, or troubleshoot network issues, all without human micromanagement.


Visual Agent

A step beyond a plain avatar. A Visual Agent is an avatar combined with a connected AI Agent capable of real-time video engagement. This allows the character to listen, think, and respond naturally in live two-way conversations. Think of it as a customer‐service rep who lives inside your app or kiosk.

LLM (Large Language Model)
A generative AI model trained on vast text corpora. When you plug an LLM into your system, it supplies the conversational intelligence that drives an AI Agent or Visual Agent; enabling nuanced, context-aware dialog.

API (Application Programming Interface)
The set of endpoints your software calls to create, control, and stream avatars. D-ID’s real-time streaming API, for example, delivers up to 100 FPS video and hooks into any LLM or NLU engine, making it the connective tissue between your logic and the Visual Agent on screen.

Mapping the AI Avatar Landscape

There’s no one-size-fits-all solution. Most AI avatar tools fall into one of four categories:

All-in-One Avatar Creation Platforms These are designed for simplicity and speed. You input a script, choose an avatar, and generate a video. Great for marketing teams, internal communications, and L&D content.

• Example Platforms: D-ID, Synthesia, HeyGen, DeepBrain

Text-to-Video Generators These models generate cinematic, stylized clips from text, images, or motion input. They’re powerful for storytelling, creative exploration, and concept development, but not yet suitable for reliable speech or lip-sync accuracy in enterprise settings.

• Example Platforms: Runway, Pika, Sora

API & SDK-Driven Platforms Ideal for developers and product teams. These platforms provide real-time avatar capabilities and deep integration hooks for apps, kiosks, or web tools.

• Example Platforms: D-ID API, Soul Machines, Heygen, Inworld AI

Conversational AI Avatars This emerging category is designed for intelligent, back-and-forth communication. These avatars can carry on real-time conversations by connecting to a large language model or AI agent like ChatGPT, Copilot, or your own assistant. The result: digital humans that feel helpful, responsive, and alive.

• Example Platforms: D-ID, Tavus, Soul Machines

Key Players in Interactive Avatar Solutions

This section focuses specifically on platforms that support interactive, real-time avatars—tools that go beyond video generation and actually enable back-and-forth engagement with customers. These players are building visual agents designed to integrate with LLMs, respond to user input, and hold meaningful, conversational experiences.

Use cases for these platforms vary, but typically include: AI-powered customer service agents, virtual financial advisors, onboarding assistants, personalized sales concierges, healthcare navigators, and interactive training facilitators. Each one requires the ability to listen, respond, and adapt in on the spot—traits that separate interactive avatars from static video solutions.

Several players have emerged in the AI avatar space, but not all are built with enterprise needs in mind.

D-ID
Is a global leader in generative AI video and interactive avatar technology, empowering organizations to create human-like digital experiences at scale. The company’s platform spans from self-service video creation to real-time conversational avatars, enabling seamless integration with large language models and enterprise systems. Trusted by Fortune 100 companies, D-ID’s technology is used across marketing, customer service, learning, and internal communications to make digital interactions more personal, engaging, and accessible. With a developer-friendly API and Creative Reality Studio, D-ID bridges the gap between video and conversation—bringing the face of AI to life.

HeyGen
Provides a streamlined interface for video-based avatars and localization. Security-wise, HeyGen is SOC 2 and GDPR compliant and makes clear that customer data is not used to train its models. However, further details on fine-grained enterprise controls, access management, or audit tooling are limited in public-facing documentation. It’s mostly used for content generation, with limited real-time capabilities and less focus on interactive experiences. While it offers an API and basic integrations, the platform is better suited for one-way video outputs rather than live CX engagement.

Tavus
Focuses on delivering AI-powered digital avatars for live interactions. While Tavus emphasizes a security-first design and offers enterprise-grade SLAs, it does not currently list formal compliance certifications such as SOC 2 or ISO 27001. Enterprises should request documentation on their security practices during evaluation. With an emphasis on dynamic communication rather than static video, Tavus enables companies to deploy personalized, on-brand virtual agents across channels. Their API and developer-first mindset make it relatively straightforward to embed these avatars into custom workflows. That said, the platform is still evolving in terms of breadth and enterprise-ready tooling, and may require additional customization for complex deployments or high-scale scenarios.

Soul Machines
Offers a visually elaborate solution, building 3D animated avatars with reactive facial expressions. Soul Machines is GDPR-aligned and partners with secure cloud infrastructure providers, such as AWS and Azure. However, it does not publicly list certifications like SOC 2 or ISO standards, and enterprises should vet compliance details directly. The implementation is complex, the infrastructure demands are significant, and the costs often outweigh the value for typical enterprise deployments. For most organizations, the barrier to entry is too high, and integration into existing CX systems is cumbersome.

UNITH
Offers digital humans that support conversational AI, primarily through its interFace platform. UNITH claims to offer enterprise-ready APIs and deployment controls, but does not currently publish detailed security documentation or third-party certifications. For regulated industries, direct assessment of their privacy and data handling policies is recommended. These avatars can be embedded into websites, apps, and services to guide users, answer questions, or serve as interactive brand representatives. UNITH promotes a no-code interface and API access, which makes it accessible for non-technical teams while still offering integration capabilities. While flexible, it remains to be seen how the platform handles highly complex enterprise requirements in areas like real-time responsiveness, deep customization, or global scalability.

Why D-ID is the Enterprise Choice

D-ID offers the right blend of usability, flexibility, and enterprise performance. Our platform was purpose-built for global organizations that need to deliver consistent, human-like interactions at scale, without compromising on security or speed.

1. Built for Integration

At D-ID, everything starts with the API. Whether you’re building avatar-powered customer agents, embedding visual assistants into websites or mobile apps, or integrating with internal systems, our platform is engineered to fit your stack. You can connect D-ID to your existing NLU engine, CRM, or contact center with minimal lift.

We also support non-technical teams with integrations into tools like PowerPoint, Canva, and LMS platforms. Teams can create avatar-led content in minutes, without needing to code.2. Enterprise-Grade Security & Privacy

2. Enterprise-Grade Security & Privacy

Security isn’t an afterthought. It’s the foundation. D-ID is SOC 2 certified and complies with GDPR, as well as multiple ISO standards (27001, 27017, 27018, 27701). We implement content moderation, watermarking, and strict access controls to prevent misuse.

Unlike some vendors, we never use your data to train our models. Whether you’re in finance, healthcare, or any compliance-heavy sector, you can rely on D-ID to meet and exceed your internal security requirements.

3. Real-Time Interaction, Delivered

We go beyond video generation. D-ID’s real-time streaming avatars let your AI interact with users through natural, responsive video. Connect any LLM or dialog system to our streaming API, and deploy lifelike avatars that respond in real-time.

This opens the door for 24/7 visual agents that feel intuitive and engaging, available in over 120 languages, with expressive facial movement, high-quality voice output, and lightning-fast response time.

4. Proven Scale and Reliability

Over half of the Fortune 100 already use D-ID. Whether you’re rolling out internal training, external support visual agents, or marketing videos across multiple regions, our infrastructure is built to support it. We deliver videos at up to 100 frames per second and process millions of requests each month.

From a pilot to a full global roll out, D-ID is ready to grow with you.

5. Support That Doesn’t Sleep

We provide 24/7 support to all API and Studio customers. Our team includes technical support engineers, onboarding specialists, and dedicated account managers for enterprise clients. We’re with you before, during, and after implementation, helping you optimize, troubleshoot, and scale.

Final Thoughts

There are a lot of great tools out there. If you’re experimenting or creating niche experiences, mixing and matching them can work. But if you’re leading a team at scale, managing compliance, and accountable for results, the stakes are higher.

D-ID was built for you. We combine a powerful, mature API with real-time capabilities, world-class compliance, and dedicated support. Whether you need to launch quickly or build a deeply customized avatar solution tied to your own AI stack, D-ID is the partner to help you get there.

If you’re ready to elevate your brand by implementing avatar videos or interactive avatars, choose D-ID.

The post Navigating the AI Avatar Landscape: A 2026 Guide for Enterprise Leaders appeared first on D-ID.

Picture a digital version of the real world. It looks real but it also feels alive. It reflects everything from machines to environments and people, constantly changing with live data. That’s what real-time digital twin technology is all about.

Unlike regular simulations that capture a specific moment in time, real-time digital twins are always listening, learning, and adjusting. Every second, new data from sensors, devices, and AI systems reshapes them, creating a living copy of reality. This helps them predict outcomes, identify problems, and support quick, data-driven decisions.

Across many industries — from factories to smart cities, energy grids, learning and healthcare — real-time digital twins are transforming how organizations perceive and engage with the world around them. They combine data with intelligence to achieve an awareness comparable to that of a human, thereby bridging the gap between the virtual and physical worlds.

This article will delve into what real-time digital twins are, why they matter, and how they’re transforming the modern business landscape.

What Is a Real-Time Digital Twin?

The idea might sound like something out of a sci-fi movie, but it’s all about data. A real-time digital twin takes information from sensors, machines, and software, turning the constant activity in the real world into a lively digital copy. 

But this isn’t just a one-way street, it’s more like a back-and-forth conversation, actions, leading to reactions. When something changes in the physical world, the digital twin updates right away. If it spots a pattern or something unusual, it can provide insights or even kick off automated actions in reality.

This creates a steady flow of feedback that mixes real-world data with AI smarts. It allows organizations to try out different scenarios, test solutions, and make informed decisions before taking any action. 

In real-life situations, digital twins can represent everything from factory setups and energy systems to entire cities or even people’s behaviors. They offer a single, changing source of truth. This helps teams understand not just what is happening, but also why it is happening and what might happen next.

By combining data, analytics, and intelligence into one adaptable system, real-time digital twins copy reality and make it easier to measure, predict, and improve. 

Benefits of Real-Time Digital Twin Systems

The rise of real-time digital twins is a major step forward in how organizations see, manage, and improve their operations. Here’s how they create a measurable impact:

Live Monitoring & Full Transparency

A real-time digital twin gives companies a clear and constant view of their assets, such as production lines, logistics networks, energy systems, and smart buildings. You can observe every small change, movement, and problem as they occur. This leads to faster responses, early issue detection, and better overall performance.

Predictive Insights & Preventive Maintenance

When AI meets live data, monitoring becomes foresight. Subtle changes in vibration, pressure, or temperature can indicate potential breakdowns long before they occur.  By predicting maintenance needs, organizations can reduce downtime, extend the lifespan of their assets, and improve reliability.

Risk Mitigation & Cost Efficiency

Simulating real-world scenarios in a digital environment allows teams to safely test decisions and identify risks early on.  Whether modelling new product designs or infrastructure resilience, real-time twins can prevent costly failures, reduce waste, and optimize operational spending.

Agile Decision-Making & Collaboration

A continuous flow of real-time data both informs and empowers. When combined with agentic AI systems (autonomous models that can reason, act, and adapt), digital twins become intelligent decision partners. They support collaboration between people, AI, and data, ensuring every action is fast, aligned, and evidence-based.

In short: real-time digital twins visualize information and then activate it.
By combining live data, intelligence, and interactivity, they turn organizations into living, learning ecosystems that evolve with clarity, confidence, and speed.

→ Learn more about agentic AI in our Agentic AI glossary entry.

Real-Time Digital Twin Examples & Use Cases

The true impact of real-time digital twins becomes clear when theory meets action. In various industries, these smart replicas are changing how organizations monitor, simulate, and improve their environments.

Manufacturing & Industry 4.0

Manufacturers quickly embraced the trend of real-time digital twins. By connecting machines, sensors, and production lines, they get a live, 360° view of everything happening. They can spot bottlenecks right away, predict maintenance needs before problems occur, and adjust production schedules in real time. For example, in car manufacturing, these digital twins can notice small changes in a robot arm’s performance. This helps prevent downtime and saves a lot of money in lost productivity.

Manufacturing use cases are well illustrated in SAP’s blog: Digital Twins at Work

Smart Cities & Infrastructure

City planners are becoming skilled at using digital twins to keep our towns running smoothly. They use real-time data from road sensors, weather information, and public transport systems to manage traffic and energy use. This helps them predict traffic jams, redirect vehicles when needed, and even understand how new construction projects will impact the area before they begin. The result is cities that are more responsive and sustainable, meeting the real needs of residents.

​​Urban digital twins are addressed in Snap4City’s Smart City Digital Twin Framework

Healthcare & Life Sciences

In healthcare, real-time digital twins are making a huge difference and even saving lives. Hospitals are using them to monitor equipment, predict how patients might respond to treatments, and tailor care specifically to each individual. Wearable devices send constant data into these personalized digital twins, which helps catch issues early and provide precise care. For instance, a digital version of someone’s heart can quickly respond to changes in their blood pressure or medication. 

Deep research on AI + digital twin in medicine: https://www.nature.com/articles/s41746-025-01874-x?

Energy & Sustainability

Energy companies are using digital twins to maintain stable power grids and manage renewable energy sources more effectively. By gathering real-time data from wind turbines, solar farms, and smart meters, they can predict energy needs and adjust power distribution promptly. This results in fewer emissions, less waste, and more reliable access to clean energy.

Enterprise Operations & Training

In the enterprise world, digital twins are redefining learning and communication.
AI-powered digital humans can mirror real employees, train teams, and interact naturally in real-time. It’s where technology meets emotion, and where D-ID’s interactive agents bring digital twins to life, turning communication into a two-way, human-like experience.

Considerations for Real-Time Digital Twin Deployment

Creating a real-time digital twin involves building a resilient, intelligent ecosystem.
The following five factors are key to ensuring success:

1. Infrastructure & Data Integration

Real-time twins rely on constant, high-quality information. This needs the right combination of IoT devices, edge computing, and cloud infrastructure. A twin can only operate effectively with the systems that support it. So, invest in fast and dependable networks to keep accuracy and speed.

2. Data Accuracy & Calibration

Even the smartest twin is only as good as its data. Regular calibration keeps digital and physical systems in sync. Create feedback loops to check results and improve the model for trust and accuracy.

3. Security & Compliance

Digital twins often handle important data. That’s why cybersecurity and regulatory compliance must be included at every level. Encryption, access control, and anonymization protect data integrity. Frameworks like GDPR help maintain user trust.

4. Human–AI Collaboration

Digital twins reach their full potential when paired with agentic AI, intelligent systems that can reason, act, and adapt. This combination allows humans to delegate complex tasks, respond more quickly, and make smarter, data-driven decisions.

5. Scalability & Future-Readiness

Start small. Scale smart. Pilot projects show data bottlenecks and process gaps before expanding. As AI evolves, flexible architectures will let digital twins grow. They will integrate new data sources, visualization tools, and even lifelike digital humans.

Conclusion

Real-time digital twins are the next big thing in smart technology. They don’t just model what’s happening; they actually participate in it. By learning, adapting, and interacting in real-time, they allow organizations to make quicker decisions, work smarter, and combine technology with human insight. 

The possibilities are vast. They can improve factories and energy networks, enhance healthcare, and provide better customer experiences. When combined with human-like AI, such as realistic digital humans and intelligent systems, digital twins turn into more than just analytical tools; they become smart partners in solving challenges. 

At D-ID, we are exploring that very intersection, where AI, data, and human presence come together to create digital experiences that are more connected, emotional, and alive.

Discover how D-ID brings real-time intelligence and emotion together 

The post Real-Time Digital Twin Examples & Use Cases appeared first on D-ID.

These days, avatars can be anything from amazingly lifelike AI presenters to playful cartoon creatures. They are all full of flexibility and expressiveness. These captivating technologies are moving beyond social media and gaming to have a profound impact on customer service, education, and business communication as AI avatar technology continues to develop rapidly. The future has arrived, and meaningful engagement is key!

The Relevance of Digital Avatars

What exactly is a digital avatar?

A digital avatar is an online version of you or a character you can use. In the past, avatars were simple two-dimensional icons or profile pictures. Now, thanks to artificial intelligence, we can create AI-generated avatars that move in a realistic way, talk, and express emotions. This makes online conversations more enjoyable, personal, and human.

Creating avatars that either represent a brand’s identity or seem like real individuals is simple with today’s platforms. Without the need for cameras or production teams, businesses can create virtual spokespeople who can deliver presentations, speak multiple languages, and explain complex subjects.

Learn more about AI Agents vs. AI Avatars and how both technologies shape the future of human-AI communication.

The evolution of avatar technology

After starting in gaming, avatars later showed up in chatbots, messaging apps, and virtual reality environments. But everything changed with the rise of AI. These avatars transformed from simple images into interactive storytellers. Machine learning enabled them to speak and move realistically as well as understand context. AI-powered avatars are becoming more important for businesses that want to connect with their global employees in a meaningful and caring way.

Why digital avatars matter

Amidst endless emails, calls, and virtual meetings, genuine connections often get lost. Digital avatars bring back the human element. They combine clarity, consistency, and emotion to make digital communication feel more engaging and personal.

Companies aren’t using avatars just for novelty — they’re solving real challenges: scaling communication, saving time, and keeping their brand voice consistent across markets. By bringing warmth and presence back into digital interactions, avatar technology helps organizations connect with employees, customers, and learners in a way that feels genuine and memorable.

Practical Applications of Digital Avatars in Enterprises

AI-generated digital avatars are changing how businesses communicate, educate, and interact with their audiences. They mix realism, scalability, and emotional presence to turn regular information into meaningful experiences. Here’s how you can use them:

1. Customer Service and Support

Imagine being welcomed by a friendly, lifelike representative who understands your needs and truly cares about your concerns. That’s the interesting part about AI-generated avatars in customer service. 

Brands are using avatars as digital helpers to guide users through troubleshooting, explain their products, and offer support after purchases. Unlike basic text bots, these avatars show empathy through their tone, gestures, and expressions, making the experience feel more personal. They are available 24/7, can speak multiple languages, and maintain the same quality no matter where you are.

2. Employee Training and Learning & Development

In corporate learning, engagement is everything. Organizations now use AI-generated avatars as on-screen trainers and narrators to turn static lessons into dynamic, video-based content. Studies reveal that expressive virtual avatars improve both knowledge retention and emotional connection — making learning feel more human.

With D-ID, teams can quickly create avatars that act as trainers or guides explaining complex topics step by step. These avatar-led videos boost retention and make training accessible across global teams.

3. Brand Storytelling and Marketing

In marketing, attention is scarce, and avatar technology helps brands stand out. AI avatars can introduce new products, explain features, or tell brand stories in multiple languages. Since they are digital, updates are easy, which ensures consistency across campaigns. Some companies even create a permanent “virtual brand face,” a recognizable avatar that builds trust and familiarity worldwide.

For more tips on using avatars in your marketing content, explore the D-ID Marketing Suite

4. Global Communication and Campaigns

Large organizations often struggle to deliver a unified message across languages and time zones. AI-generated avatars make this simple: executives can record one message and automatically translate it into multiple languages, with accurate lip sync and emotion.

Internally, avatars make CEO messages, company updates, or safety briefings feel personal and engaging. Integrated with platforms like LMS or CRM systems, they streamline communication at scale.

The Technology Behind AI-Generated Digital Avatars

Whenever you see a digital avatar speaking naturally or smiling at the right moment, it is the result of a complex mix of AI technologies. What used to require studios and voice actors can now be done in seconds, thanks to modern avatar technology.

1. The AI Engine

At its core, there is a network of generative AI models that handle visuals, speech and language. These systems map facial features, motion and emotion in order to synchronise movement and voice perfectly.

 D-ID’s deep-learning technology matches lip movement, tone, and expression in real time, creating avatars that look and feel human.

2. Facial Animation and Motion Synthesis

Neural networks learn how facial muscles behave when expressing emotions. When text is entered, the system converts it into synchronized eye, mouth, and body movement. Subtle gestures make AI-generated avatars feel alive — not robotic.

3. Text-to-Speech (TTS) and Voice Generation

Voice gives an avatar its personality. Modern TTS models, trained on thousands of hours of speech, produce natural and emotional voices. Brands can choose from different tones or even replicate an existing voice to match their spokesperson. This flexibility helps companies create avatars that truly represent their brand around the world.

4. Real-Time Rendering and Responsiveness

Real-time rendering enables avatars to be animated instantly, eliminating the need for pre-rendered video. This enables the creation of interactive experiences where users can ask questions and receive immediate responses.
It’s the foundation of interactive AI avatars and AI agents that combine visuals with large language models (LLMs) for natural two-way dialogue.

5. Retrieval-Augmented Generation (RAG)

RAG ensures avatars provide reliable, context-aware information. Enterprise avatars can pull data directly from internal documents, product specs, or training materials. This guarantees that their responses are relevant.

6. The Result

When facial animation, neural voice synthesis, real-time rendering, and RAG work together, the outcome is a lifelike, scalable, and emotionally intelligent communicator. With D-ID, companies can create hundreds of personalized videos or interactive agents in minutes — no cameras or studios required.

Best Practices for Creating and Using Digital Avatars

While it’s easy to create avatars, success depends on how strategically they’re designed and used. Here’s how to make the most of them.

1. Personalization That Feels Authentic

The most effective AI-generated avatars reflect your organization’s tone and culture.

• Customer-service avatars should sound empathetic.
  
• Trainers should project confidence and energy.
  
• Brand ambassadors may adapt their language and style for each region.
  Customization — from gestures to voice timbre — makes avatars feel genuinely human.

2. Keep Brand Consistency

Your digital avatars are extensions of your brand identity. Align tone, visuals, and setting with your style guidelines. Use similar designs across teams to maintain cohesion.

3. Accessibility and Inclusivity

AI avatars can improve communication by providing subtitles, multilingual voice options, and simpler scripts. This makes content more accessible. It also broadens your audience and shows your company’s commitment to accessibility.

4. Integrate Avatars Seamlessly

To maximize efficiency, embed avatar technology into daily workflows:

• Connect avatars with LMS or CRM systems.
  
• Automate onboarding, FAQs, or training updates.
  
• Use templates to standardize video creation.
  

5. Be Transparent and Ethical

Disclose when an avatar is created by AI. Never use avatars to mislead or impersonate real people. Ensure that all data used for training or creation is protected. Being clear builds trust over the long haul.

6. Measure and Optimize

Track engagement, retention, conversions, and sentiment to evaluate impact. Continuous optimization helps refine both design and messaging.

If you’re considering building your own avatar, check out our guide on choosing the right AI avatar creation tool to find the best fit for your goals and content type.

Conclusion

AI-generated digital avatars are changing how organizations communicate. They turn everyday information into interactive and engaging experiences. Whether they help customers, train employees, or promote a brand, these avatars blend emotion, efficiency, and accessibility in a fresh way.

As this technology continues to improve, so do its possibilities, resulting in greater realism and personalization than ever before. Companies that hop on board now are really shaping the future of communication. 

Want to create avatars that truly represent your brand? Find out how D-ID helps organisations to create realistic, interactive avatars that improve communication by making it faster, smarter, and more human.

The post How Are AI-Generated Digital Avatars Used? appeared first on D-ID.

Now, a new chapter begins: simpleshow is joining D-ID. For over 15 years, simpleshow has been a trusted partner for enterprises around the world, transforming complicated topics into simple, memorable stories through explainer videos.

“Our mission has always been to simplify complex information so that everyone can understand it — with ease and a touch of storytelling,” says Karsten Böhrs, CEO of simpleshow.

Together, D-ID’s avatars and simpleshow’s storytelling platform create a powerful synergy: communication that is both clear and interactive, scalable and personal.

“This merger is about taking communication to the next level — combining simplicity and storytelling with interactivity and human connection,” adds Gil Perry, CEO of D-ID.

On September 16, 2025, the merger of the two companies was officially announced. Soon, operations will run under the D-ID name uniting the best of both worlds:

• D-ID’s real-time interactive visual agents and scripted avatars
  
• simpleshow’s enterprise-scale video storytelling platform
  

This combination opens entirely new possibilities for Learning & Development, marketing, HR, sales, and internal communication.

What stays the same

The D-ID products you already use remain fully available and work exactly as you know them today. Whether it’s Interactive Avatars for real-time conversations, the Creative Reality Studio for generating lifelike videos, or integrations into your own platforms and workflows — all of these tools continue without interruption. You can keep building customer interactions, training modules, or marketing experiences with the same reliable technology you already trust.

Beyond the products themselves, nothing fundamental about your existing agreements will change. Contracts, pricing models, SLAs, and support contacts remain exactly as before, ensuring stability and predictability. The same applies to data, privacy, and security: all commitments stay in place, with no adjustments to data handling or residency without your explicit approval.
 

What gets better

With simpleshow joining the D-ID family, customers gain access to a completely new dimension of video creation. simpleshow video maker, trusted by enterprises worldwide, now becomes part of the offering, adding simplicity and speed to professional video production.  Equipped with powerful AI features, the tool can automatically condense complex topics into easy-to-understand videos, making professional storytelling more accessible than ever.

This means more creation options than ever before. Real-time interactive avatars can now be paired with AI-scripted explainer videos, enabling both live, personal interaction and scalable storytelling at the same time.

Customers also benefit from a richer set of resources. The extensive simpleshow content libraries and workflows provide ready-to-use templates, illustrations, and structures that make video projects faster to produce and more engaging to watch.

Finally, it all comes together under one roof. Instead of managing multiple vendors, enterprises can now rely on a single partner for a full spectrum of communication needs — from multilingual explainer videos at scale to live, face-to-face digital humans powered by D-ID.

“We’re combining our leading avatar technology with simpleshow’s incredible storytelling tool. This unlocks entirely new opportunities for companies worldwide,” says Gil Perry.

Why the combination matters

The strength lies in integration: D-ID avatars bring interactivity and dialogue, while simpleshow videos deliver clarity and storytelling. Together, they redefine how enterprises connect with employees, customers, and partners:

• HR & Onboarding: A video introduces processes. A D-ID avatar coach answers employee questions in real time.
  
• E-Learning & Training: Explainer videos teach the basics. An avatar trainer follows up with quizzes or role plays.
  
• Customer Service: Videos explain key functions. A service avatar guides users step by step, responding instantly.
  
• Sales & Marketing: Product videos highlight benefits. Live avatars adapt the pitch to different audiences.
  
• Internal Communication: A video explains a change process. An avatar spokesperson turns it into a dialogue.

Conclusion

With simpleshow joining D-ID, the most complete solution for enterprise communication is taking shape. Clear explainer videos provide structure and storytelling, while interactive avatars bring dialogue and human connection.

For companies, this combination translates into communication that is simpler, more personal, and more efficient — powered by one trusted partner: D-ID.

The post More impact for your communications: D-ID expands with simpleshow acquisition appeared first on D-ID.

If you’ve ever wished your chatbot could look you in the eye, smile, and hold a natural conversation, you’re in the right place. D‑ID’s Visual Agents make that possible. No cameras, no crews, just a few clicks (and the right prompts) in the Studio.

Visual agents are interactive AI avatars that are live, conversational, and powered by real‑time AI. They combine human presence (through avatars) with AI intelligence (through live conversational models).

Click this link to speak with Amber, a D-ID visual agent.

This guide walks you through creating your first visual agent, prompt by prompt. Whether you’re welcoming website visitors, answering FAQs, or just showing off what’s possible, you’ll learn what each Studio field does, how to fill it, and how to get a visual agent that feels alive, on brand, and ready to engage.

Tab 1: Appearance – Choosing the Face of Your Visual Agent

Your visual agent’s appearance is its first impression. It’s what makes users stop, pay attention, and feel like they’re talking to a person, not just a piece of software.

In D‑ID Studio, the Appearance field is where you select or create your agent’s avatar.

Two Ways to Set the Appearance

1. Stock Avatars

• What they are: A curated library of ready‑made digital people.
• Best for: Quick setup, testing new agents, or use cases where the face doesn’t need to match a specific brand personality.
• Pros:
  • Instant access – pick and go.
  • Wide variety of demographics and styles.
  • No production work required.
  • Studio-quality trained on professional actors
• Cons:
  • Not unique to your brand.

2. Custom Avatars

• What they are: Your own uploaded images or videos turned into an avatar.
• Best for: Brand‑aligned Agents (e.g., spokesperson, team member, influencer).
• Pros:
  • Fully unique to you.
  • Builds stronger brand familiarity.
• Cons:
  • Requires you to create or source media.
  • Premium+ tiers required for video-based uploads.

Two Formats for Avatars

Regardless of whether you choose stock or custom, you can pick the format:

Photo‑Based (Standard)

• How it works: Uses a single still image to animate speech and expression.
• Best for: Fast performance, lightweight interactions, simple informational Agents.

Video‑Based (Premium / Premium+)

• How it works: Uses a short video clip for richer animation, more natural expressions, and subtle movements.
• Best for: High‑impact experiences like sales demos, high‑touch customer service, or brand representation.

Pro Tip: If your Agent is customer‑facing or plays a prominent role on your site/app, invest in Premium+ custom avatars.

Tab 2: Agent Details & Preview Mode – Define How Your Visual Agent Acts

Once your visual agent has a face, the next step is to give it a personality framework, the key details that shape how it’s perceived. You’ll also notice a window appear on the right side of the Studio. This is Preview Mode, your real‑time testing space. As you fill out the fields on this tab, the panel on the right lets you chat with your visual agent and see how your inputs affect its responses in real time. In preview, the visual agent won’t be animated, but it will respond in text so you can test tone, style, and behavior before going live.

Agent Name

• What it does: This is the name displayed to users during interaction.
• Best practice:
  • Keep it short, friendly, and easy to pronounce.
  • Use first names only (“Amber,” “Alex,” “Emma”) for accessibility.
  • Avoid quirky or joke names unless they fit your brand tone.
• Why it matters: The name is the first anchor point for building rapport, it’s small but powerful.

Language & Voice

• What it does: Sets how your Agent sounds and in which language(s) it communicates.
• Best practice:
  • Match your audience’s primary language.
  • Pick a voice that fits the Persona, warm and approachable for casual interactions, calm and professional for support roles.
  • Stick with one voice per Agent for consistency.
• Why it matters: Voice and language shape tone, clarity, and trust in every conversation.

Role

• What it does: Defines the visual agent’s “job description” in a single sentence.
• Best practice:
  • Format as “You are [name], a [tone/role] who [main function].”
  • Be specific. Avoid vague roles like “AI assistant.”
  • Example: “You are Chloe, a friendly customer support specialist who helps users troubleshoot and set up our product.”
• Why it matters: Role sets the scope of interaction, keeping the visual agent focused and on-brand.

Pro Tip: These five fields: Appearance, Name, Language, and Role work together. The moment a user says “Hi,” your visual agent’s identity, tone, and purpose should feel instantly clear.

Instructions

If the Appearance is your visual agent’s face and the Voice is how it sounds, then Instructions are the brain. This field tells your visual agent exactly how to behave.

Why the Instructions matter

Instructions are like a script + employee handbook for your visual agent:

• They define the Agent’s identity (who they are, how they talk).
• They create boundaries (what they will and won’t discuss).
• They shape conversation flow (how they guide and pivot topics).
• They ensure tone consistency (so every response sounds on brand).

How to Structure the Instructions

Organize your Instructions into clear mini‑sections. The Studio doesn’t require this formatting, but the AI will respond better to a structured approach.

1. Persona (1–2 sentences)

Give your Agent a backstory that sets tone and style.

• What to include: Name, age (optional), appearance description, location or background, and their “role” (what they do for users).

2. Key Rules

These are the golden rules for every answer.

• Common rules:
  • Keep responses short (≤ 400 characters).
  • No bullet points or numbered lists (to keep speech natural).
  • Use only conversational text – no stage directions, no emojis.
  • Light natural fillers allowed (“uh,” “well,” “you know”).

3. Off‑topic Handling

Your visual agent may get curveball questions. Instruct it on how you want it to respond.

• Best practice: Acknowledge the question, respond briefly if possible, then pivot back to the main purpose.
• Example:
  “If asked about unrelated topics (e.g., aliens), respond with humor and steer back: ‘Aliens? Haven’t met any—yet! But I know plenty of cool spots on Earth. Want to plan a trip?’”

4. Limitations

These are the guardrails, telling the visual agent what it must not do – either because it is incapable of doing so or because it would be counter to its intended use case.

• Common limitations:
  • No singing, rapping, or sound effects.
  • Politely refuse jailbreak or off‑policy requests.
  • No real‑time web searches (not supported in studio).
  • No offers to dsiplay unsupported media types (videos, images).

5. Proactive Lead

A great visual agent doesn’t just answer questions, it guides the conversation so it feels natural and productive.

Tell your visual agent how it should maintain engagement by giving it examples:

• Ask clarifying or follow‑up questions.
  Example: “Would you like me to go into more detail?”
• Offer to provide additional information.
  Example: “I can explain how that works step‑by‑step. Want me to?”
• Suggest related topics.
  Example: “Since we covered this feature, should I show you how it connects to other tools?”
• Share a short, relevant insight or tip.
  Example: “Here’s a quick tip that might help—would you like to hear it?”
• Offer to summarize or recap.
  Example: “I can give you a quick summary of what we’ve covered. Want me to?”

6. Fallback / Uncertainty

Even the best‑configured Visual Agent will face a question it can’t answer.
How it handles these moments will define user trust. A confident fallback keeps the conversation helpful and professional. Instruct the visual agent on what it should do when it:

• Encounters a topic outside its configured knowledge.
• Lacks the data needed for a confident answer.
• Gets a vague or ambiguous question.

Best Practices for Fallback

1. Be transparent, not evasive
   • Users appreciate honesty more than generic non‑answers.
   • Example: “I don’t have that information right now, but I can direct you to the right resource.”
2. Redirect to a reliable URL
   • The Agent’s best next action is to share a helpful link, knowledge base page, FAQ, product documentation, or contact form.
   • Example: “You can find full details here: [www.example.com/support].”
3. Maintain a friendly, confident tone
   • Avoid robotic “I cannot process this” language.
   • Keep the personality consistent with the rest of the Agent.

Generic Fallback Examples

• “I don’t have the exact details, but you can check here: [URL].”
• “That’s outside my scope—our help page might have what you need: [URL].”
• “I’m not certain, but this link might point you in the right direction: [URL].”
• “I can’t confirm that, but our support resources can help: [URL].”

Pro Tip: Always make sure the URL in the fallback response is up‑to‑date and accessible, a bad link can undo the trust you’ve built.

Personality

The Personality setting controls the tone and style of your Agent’s responses.

In the Studio, you can pick from default options or write your own.

Best practice:

• Choose the tone that fits your audience and use case.
• Keep it consistent with your brand voice and the role defined in the Instructions.
• If none of the defaults fit, write a short custom description (2–3 words).

Pro Tip: Test a few sample interactions before finalizing. The right personality should make responses sound natural and on‑brand from the very first answer.

Tab 3: Knowledge Sources – Control what your visual agent knows

Conversation Mode

This setting controls how your visual agent forms responses and what information it can use.

Every visual agent is powered by an LLM (large language model). This model comes with its own built‑in knowledge, a general understanding of language, common facts, and reasoning skills. It’s broad but not connected to live internet or real‑time updates.

Conversation Mode determines how your visual agent uses that model knowledge alongside (or instead of) the information you provide.

1. Ungrounded

• What it does: The visual agent uses only the LLM model’s built‑in knowledge and the behavior you’ve defined in its Instructions.
• When to use:
  • Early testing of tone, style, and personality.
  • Agents meant for broad, generic conversations without company‑specific content.

2. Hybrid

• What it does: The visual agent combines the LLM model’s built‑in knowledge with the information you upload in the Knowledge Base. Your material is prioritized, but the model can use its general knowledge to make answers sound more natural.
• When to use:
  • When you want a conversational tone with brand‑specific details included.
  • Most onboarding, support, and general marketing use cases.

3. Grounded

• What it does: The visual agent ignores the LLM model’s built‑in knowledge for factual content and responds only with the information you’ve supplied.
• When to use:
  • When accuracy and control are critical.
  • Regulated industries or scripted experiences where every response must be based on approved material.

Knowledge Base

The Knowledge Base lets you supply your visual agent with specific information like FAQs, product details, or procedures so it can answer with brand‑accurate responses. There are two ways to provide your visual agent with knowledge: inputting text directly (recommended) and uploading external files.

Pro Tip: Think of these files as a spoken resource write them in natural, complete sentences so your visual agent can read them aloud clearly.

Creativity Level

The Creativity Level slider sets how your visual agent generates responses, ranging from highly predictable to more varied and expressive.

How It Works

• Lower settings = More predictable, focused responses.
  • The visual agent will stick closely to the facts and avoid rephrasing.
• Higher settings = More diverse, creative responses.
  • The visual agent may rephrase explanations, add examples, or vary its wording.

LLM selection

The LLM (Large Language Model) is the engine that powers how your visual agent understands and responds. Choosing the right model can affect response speed, accuracy, and tone.

Available Models in Studio

• GPT‑4o Mini (Default)
• GPT‑4o Global
• GPT‑3.5 Turbo

Note for API Users
If you’re connecting your visual agent via API, you can select any LLM you want not just the Studio defaults. This allows optimization for speed, cost, or model preference depending on your deployment needs. Visit our documentation to learn more.

Tab 4: Chat Settings – Shape how conversations start and flow

Welcome Message

The welcome message is the first thing users see when they meet your visual agent. It sets context for the interaction, explaining who the visual agent is, what it can help with, and what kind of conversation to expect. A well‑written welcome message helps users quickly get into the conversational flow and feel confident engaging.

Best practices:

• Keep it short but informative. Introduce the visual agent’s role.
• Set expectations for what it can do.
• Match the tone to the personality you’ve chosen.

Conversation Starters

Conversation starters give users clear, clickable prompts they can select to begin the interaction. They don’t just make it easier to start they also provide context by showing what kinds of questions or tasks the visual agent is best equipped to handle.

• Why it matters:
  • Helps users feel confident about what to ask.
  • Demonstrates the visual agent’s capabilities immediately.
  • Sets the scope of the conversation from the start.
    
• Best practice:
  • Include up to 4 prompts focused on common or high‑value questions.
  • Frame them in natural language so they feel conversational.

Topics to Avoid

These define clear boundaries for what your visual agent won’t discuss.

• Why it matters:
  • Keeps interactions focused on the intended purpose of the visual agent.
  • Prevents users from steering into areas that are irrelevant, off‑brand, or high‑risk.
  • Helps the visual agent maintain tone and trust by avoiding inappropriate or sensitive areas.
• Best practice:
  • Add topics that are outside the visual agent’s scope or pose compliance risks.
  • Common examples: Pricing, competitors, legal issues, internal policies, or unsupported integrations.
  • Keep the list focused. Don’t over‑restrict unless necessary, as too many blocked topics can frustrate users.

Max Response Length

Max response length sets the upper limit for how long your visual agent’s answers can be. While it may seem like a simple character limit, it actually shapes the pacing and tone of the conversation.

• Why it matters:
  • Shorter responses keep the interaction feeling snappy and conversational, like a real back‑and‑forth.
  • Longer responses can work for tutorials, explanations, or guided walkthroughs, but risk slowing the flow if overused.
  • Striking the right balance ensures the visual agent sounds natural, not robotic or overwhelming.

Pro Tip: Test your visual agent in Preview Mode after each major change. Small adjustments before launch can make a big difference in user experience.

You’ve got the tools, the settings, and the best practices—now it’s time to create. Whether you’re building a friendly guide, a knowledgeable support companion, or a persuasive sales assistant, your visual agent can transform the way people interact with your brand.

Start small, test often, and refine as you go. The more you work with your visual agent, the more natural, helpful, and uniquely “yours” it will become. If you encounter any difficulties, our support team will be happy to assist. Start by visiting our Help Center.

Open D‑ID Studio and start building your first visual agent today.

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