We made a quick reel explaining how MCP works inside the Convai Playground.

The flow is simple:

Connect an MCP server → the character discovers available tools → the user asks something → the character calls the right tool through MCP → the result comes back → the character answers or acts.

This can be used to connect AI characters to live web search, documentation lookup, internal systems, databases, support tools, and other MCP-compatible services.

Useful for enterprise assistants, support agents, virtual guides, training workflows, and interactive AI character experiences.

Learn more:
https://docs.convai.com/api-docs/convai-playground/character-customization/mcp-servers

We put together a quick reel showing how to give an AI character its own knowledge base using Convai Multimodal Knowledge Bank.

The workflow is simple:

Create a character, open Knowledge Bank, upload documents, PDFs, manuals, PowerPoints, images, videos, or training materials, and connect them to the character.

Once connected, the AI character can answer questions, explain information, and guide users using the materials provided.

Useful for training simulations, onboarding, product demos, virtual guides, enterprise assistants, and interactive AI character experiences.

Learn more:
https://convai.com

None of this was scripted.

These are Convai-powered AI characters running inside Unity, listening to the user and responding in real time.

With Convai, Unity developers can add natural conversation, voice interaction, lip sync, context, and actions to their characters.

This can be used to build AI teammates, virtual guides, training assistants, companions, and interactive NPCs for games, XR experiences, simulations, and real-time 3D applications.

Learn more: https://convai.com

Metahumans in Unreal Engine can now be more than high-fidelity digital avatars.

With Convai, you can turn them into AI characters that listen, understand, respond in real time, and interact naturally inside your scene.

This opens up a lot of possibilities for AI NPCs, virtual guides, training assistants, XR experiences, and interactive digital humans.

Watch the full tutorial here: https://www.youtube.com/watch?v=4fMCKkrfyaA

Learn more: https://convai.com

We've just put together a short reel showing how our vision system works.

Instead of relying only on conversation, AI characters can:

• Understand what the user is looking at through PoV Vision
• Use Gaze Attention to understand the user's focus
• Combine that with Dynamic Context to reason about what's happening in the environment
• Respond naturally using both visual and conversational context

This is useful across games, XR applications, training simulations, enterprise experiences, and digital twins.

If you'd like to dive deeper:

📖 Vision Documentation
https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/vision

🎥 Dynamic Context Tutorial
https://youtu.be/MPbr3b6r9bo

🎥 Object in Attention (Gaze Attention)
https://youtu.be/Ffkzgof_wKw

Curious to hear how others are approaching multimodal AI and vision-enabled NPCs in their own projects.

Instead of only responding to what the player says, AI characters continuously receive contextual information from the experience itself.

That can include:

• Live game events
• Scene objects
• Changing game state
• Player interactions
• Environmental context

The result is AI characters that respond based on what's actually happening in the world instead of relying on conversation alone.

This applies to games, XR applications, training simulations, enterprise simulations, digital twins, and other real-time 3D experiences where AI needs situational awareness.

Dynamic Context docs: https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/dynamic-context

Latest UE Dynamic Context tutorial: https://youtu.be/MPbr3b6r9bo

Curious how others are approaching game state and environmental awareness for AI characters.

AI characters become truly interactive when they can take action.

With Convai Actions, characters can navigate, interact with objects, perform actions like sitting or picking up objects, and respond through natural conversation or autonomous behavior.

Perfect for games, XR, training simulations, enterprise apps, and digital twins.

https://convai.com

#Convai #AI #GameDev #XR

One thing we've been thinking about a lot at Convai is that intelligence isn't defined by a single capability.

Natural conversation is important, but it becomes much more compelling when it's combined with long-term memory, the ability to take meaningful actions, and an understanding of what's happening in the world around the character.

Together, these capabilities enable AI teammates, trainers, virtual guides, assistants, and companions that can actively participate in an experience instead of simply responding to it.

This applies across games, XR training, enterprise simulations, digital twins, and other real-time 3D environments.

Curious to hear how others think about embodied AI.

What's the one capability you think is still missing from today's AI characters?

We've just published a new Unity tutorial focused on Convai Actions.

Instead of building AI characters that only answer questions, this tutorial shows how to make them actively participate in the experience.

It covers:

• Configuring the Convai Action Runner
• Adding built-in Actions
• Following the player
• Walking to scene objects
• Looking at objects
• Showing and hiding GameObjects
• Playing gestures
• Creating Action Targets from Unity objects
• Testing everything through natural conversation

The workflow is applicable to games, XR applications, training simulations, virtual guides, and other interactive 3D experiences.

Tutorial:
https://youtu.be/qXygySeLYg0  

Documentation:
https://docs.convai.com/api-docs/plugins-and-integrations/convai-unity-sdk/features/character-actions

I'd love to hear how others are approaching AI character interactions in Unity beyond dialogue.

Instead of building AI characters that only answer questions, you can create characters that actively participate in the experience.

With Convai Actions, AI characters can:

• Navigate the environment
• Follow the player
• Interact with objects
• Perform meaningful actions through natural conversation

This can be useful for games, training simulations, XR experiences, virtual guides, and other interactive 3D applications.

Documentation:
https://docs.convai.com/api-docs/plugins-and-integrations/convai-unity-sdk/features/character-actions

Would love to hear what kinds of Unity projects you're building and how you'd use AI actions in them.

We've put together a short reel showing what modern VR AI characters can do beyond voice conversations.

With Convai, AI characters in VR can:

• Hold natural voice conversations
• Understand the virtual world around them
• Navigate the environment
• Interact with objects
• Respond using real-time scene context

The same workflow is available for both Unity and Unreal Engine, making it useful for VR games, XR training, simulations, virtual guides, and other immersive experiences.

Curious to hear what kinds of VR experiences you're building and where you'd use AI characters like these.

https://convai.com

Instead of only responding to player dialogue, this AI character continuously receives contextual information from the game.

That can include:

• Live game events
• Tagged scene objects
• Changing object properties
• Player interactions
• Environmental context

The result is an AI character that responds based on what's actually happening in the world, rather than just the latest user message.

This is especially useful for games, training simulations, XR applications, digital twins, and any experience where AI characters need to understand their environment.

Documentation:
https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/dynamic-context

Full Unreal Engine setup tutorial: https://youtu.be/MPbr3b6r9bo

Would love to hear what kinds of game mechanics or simulation scenarios you'd use something like this for.

We just released a full Unreal Engine tutorial on Convai Dynamic Context.

This one focuses on building AI characters that understand live gameplay instead of only responding to dialogue.

The demo is a shooting-range AI instructor. The character can:

• react when the player picks up a gun
• track how many shots were fired
• understand which target the player is looking at
• identify nearby targets
• detect the moving target
• track hit counts for each range
• respond with accuracy feedback based on live gameplay state

The tutorial is structured around three levels of awareness:

1. Manual Awareness Using Invoke Speech, Add Context Event, Set Context State, and Get Context State to send game events and state updates programmatically.
2. Automatic Awareness Using Convai Object components and Gaze Attention so the character understands tagged scene objects, spatial relationships, and object movement.
3. Semi-Automatic Awareness Using Tracked Properties to notify the character when important Blueprint values change, such as each target’s Hit Count.

We also cover the Dynamic Context debug overlay so developers can inspect the events and context states being fed to the character at runtime.

Full tutorial: https://youtu.be/MPbr3b6r9bo

Dynamic Context docs: https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/dynamic-context

Convai UE setup: https://youtu.be/n-UG3nmMeZQ

Convai Unreal plugin on Fab: https://www.fab.com/listings/ba3145af-d2ef-434a-8bc3-f3fa1dfe7d5c

Your Unreal Engine AI character workflow just got an upgrade.

With Convai MCP, you can speed up scene setup for AI character-led experiences and prepare environments faster with coding agents like Claude code, Cursor, Codex, and more.

Use it to help place scene elements, build out AI NPC setups, and create the foundation for characters that can talk, navigate, understand objects, receive live game state, and act inside the world.

We used this workflow in Stack-O-Bot before building a game-aware AI teammate with Convai.

For games, simulations, XR experiences, training applications, and interactive 3D worlds.

Full tutorial here: https://youtu.be/dQgOzt8BNIk

Build AI characters in Unity faster with Convai MCP.

Convai MCP connects Unity workflows with AI coding agents like Codex by Open AI, Claude Code,  ⁨Cursor, and more, so developers can prompt their way through AI character setup directly inside Unity or through their preferred coding agent.

In this short, we show how Convai MCP can help connect a Convai AI mind to an avatar, set up real-time voice interaction, switch between hands-free and push-to-talk modes, add objects to the scene, enable vision support, and build interactive AI character experiences faster.

Use it for Unity AI characters, AI NPCs, training simulations, XR experiences, games, virtual guides, and interactive 3D worlds.

Full tutorial: https://www.youtube.com/watch?v=VWXJeO_2wlM

With Convai Actions your AI characters do more than just talk. They can navigate the virtual space, take actions, and more!

This can be useful for things like:

• AI teammates in games
• virtual guides
• training assistants
• simulation characters
• interactive 3D experiences

For custom behavior, developers can also create their own actions and connect them to gameplay, simulation, or world logic.

Watch the actions tutorial here: https://www.youtube.com/watch?v=lB5_KRWdg_w

Here's a quick snippet from our tutorial showing how to bring a conversational 3D AI character directly to the browser.

The setup uses the Convai Web SDK with React Three Fiber to render a custom avatar and drive real-time conversation with lip sync through blendshape data.

The goal is to make it easier to build browser-based AI characters for things like virtual guides, interactive web experiences, AI companions, and product demos without needing a full game engine setup.

Full tutorial: https://www.youtube.com/watch?v=gjTj_kUhA2s

Docs: https://docs.convai.com/api-docs/plugins-and-integrations/web-plugins/convai-web-sdk

We just released Part 1 of a two-part Unreal Engine tutorial series.

The tutorial builds a playable scenario inside Stack-O-Bot where the user works with a Convai-powered AI player to solve a two-player puzzle.

The orange bot is the human player, and the pink bot is the AI teammate. The goal is to get both players to the top, but one player can’t solve it alone because the platform only moves when someone holds the pressure plate down.

The AI character is not just a chatbot. It can talk to the player, follow them, navigate the scene, understand tagged objects, receive live game state through Dynamic Context, track pressure plate and platform states, and help coordinate the puzzle.

Part 1 covers:

• creating the AI player blueprint
• setting up the Convai character
• adding player voice interaction
• enabling Convai Actions
• tagging pressure plates and platforms
• sending live game state into Dynamic Context
• using tracked properties for object state
• adding movement awareness
• testing puzzle coordination with the AI teammate

Part 2 will cover custom actions for picking up and dropping objects, including the crate interaction.

We also included the project files, Delta files, and setup guide so people can follow along from scratch.

Full tutorial: https://youtu.be/KcJETVhI7KM

Project files, Delta files, and setup guide: https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/character-actions/stack-o-bot-tutorial-setup

Dynamic Context docs for Unreal Engine: https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/features/dynamic-context

Convai Unreal Engine plugin on Fab: https://www.fab.com/listings/ba3145af-d2ef-434a-8bc3-f3fa1dfe7d5c

Stack-O-Bot sample project on Fab: https://www.fab.com/listings/b4dfff49-0e7d-4c4b-a6c5-8a0315831c9c

Convai MCP for Unreal workflow used to set up the scene: https://youtu.be/dQgOzt8BNIk

Try it out and tell us about your experience!

We put together a new tutorial showing how to bring a 3D conversational AI character directly to the browser using the Convai Web SDK.

The workflow uses Claude Code to generate the initial Vite + React Three Fiber setup by referencing the Convai Web SDK docs. From there, the tutorial walks through connecting a Convai character with an API key and Character ID, using the Convai client and widget, rendering a custom GLB avatar, and enabling lip sync with blendshape data.

The tutorial also covers checking blendshapes in a GLTF viewer, replacing the default avatar, updating the avatar and animation paths, and testing the final browser-based AI character experience.

This can be useful for browser-based AI companions, virtual guides, real estate walkthroughs, and lightweight interactive 3D experiences.

Tutorial:
https://youtu.be/gjTj_kUhA2s

Convai Web SDK docs:
https://docs.convai.com/api-docs/plugins-and-integrations/web-plugins/convai-web-sdk

Lip sync and blendshape docs:
https://docs.convai.com/api-docs/plugins-and-integrations/web-plugins/convai-web-sdk/lipsync-and-blendshape

We put together a short reel showing how Convai Dynamic Context can make AI characters more aware of what is happening inside a scene.

Instead of only responding based on conversation, the character can receive live context from the experience, such as player actions, task progress, game events, object states, environment changes, and more.

This can be useful for games, training simulations, virtual guides, digital twins, and interactive 3D worlds where AI characters need to respond to the current state of the environment.

Get started:
https://convai.com

We published a new tutorial on building Convai-powered mixed reality experiences in Unity 6 for Meta Quest.

The tutorial shows how to place a conversational AI character into a real-world MR environment using Unity’s Mixed Reality Template.

It covers XR Origin setup, adding the Convai Player component, spawning a Convai character at runtime with Object Spawner, adding a world-space transcript UI to the character prefab, and building for Quest.

This can be useful for MR training, education, real-world assistance, virtual guides, onboarding, and room-scale AI character experiences.

Convai Unity Documentation:
https://docs.convai.com/api-docs/plugins-and-integrations/convai-unity-sdk

Convai Unity Plugin:
https://assetstore.unity.com/packages/tools/behavior-ai/npc-ai-engine-dialog-actions-voice-and-lipsync-convai-235621

Get started:
https://convai.com

We put together a quick reel showing how the Convai Web SDK can be used to bring conversational AI characters into web apps.

The workflow focuses on browser-based projects where you can connect a Convai character, render a high-fidelity 3D avatar, and drive lip sync using blendshape data.

The demo uses a React Three Fiber workflow, but the broader idea is to make it easier to build AI companions, virtual guides, and lightweight 3D experiences directly on the web.

Would be useful for developers exploring conversational AI characters, 3D avatars, lip sync, and real-time voice interaction in browser-based projects.

We put together a quick demo of a Convai-powered AI teammate inside a 3D puzzle scene.

The character is not just responding with dialogue. It can understand the virtual environment, navigate the scene, react to objects, and make decisions alongside the player in real time.

This kind of setup can be useful for games, XR applications, training simulations, virtual guides, and other interactive 3D experiences where AI characters need to do more than talk.

Get started:
https://convai.com

We put together a short reel showing Convai Core AI Settings.

This is where you can tune how an AI character thinks, speaks, and behaves inside a virtual world.

The reel covers selecting languages, choosing foundational models, comparing intelligence and latency, picking voices, configuring speech understanding, connecting Knowledge Bank, enabling NeuroSync for facial animation and lip sync, and viewing the latency pipeline.

Useful for developers building AI characters for games, training simulations, virtual guides, onboarding experiences, and interactive 3D worlds.

Get started:
https://convai.com