Convai
Convai builds embodied 3D AI characters that see, hear, and act inside Unity, Unreal Engine, and XR worlds.
If you're shipping NPCs or VR training simulations in Unity or Unreal, Convai solves problems text-chatbot builders don't know exist — Scene Tagger tags a whole level in minutes, Convai Actions scripts object pickup and placement, and multiple AI characters can now share one Unity scene without talking over each other. The Unity MCP path into Codex, Claude Code, and Cursor is a genuine time-saver for teams already coding in those editors. Pick it when spatial awareness is the point. Skip it when the deliverable is a text interface or a website widget — you'd be paying for a 3D stack you never touch, and lighter chatbot platforms cover that job.
Verified 3d ago · liveness 72/100 · cite: rightaichoice.com/tools/convai
- Game studios building NPCs that react to player gaze, game state, and scene context in Unity or Unreal
- XR teams creating conversational characters for mixed reality training and social worlds
- L&D and simulation builders running AI roleplay training for enterprise or education
- Manufacturing and industrial trainers who need expert knowledge at the point of work
- Teams that need a plain text chatbot without 3D avatars or spatial context
- Projects with no Unity, Unreal, or Web SDK engineering capacity on hand
- Web or mobile assistant apps where perception and embodiment add nothing
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Skip Convai if your deliverable is a text chat window or website help widget with no 3D scene, no avatar, and no spatial context — you'd be buying an engine-native perception stack you never call.
Convai's pricing fits teams whose volume aligns with the published tiers. Compare against the alternatives listed below for stage-specific value.
In short
Convai — Convai builds embodied 3D AI characters that see, hear, and act inside Unity, Unreal Engine, and XR worlds. Best for Game studios building NPCs that react to player gaze, game state, and scene context in Unity or Unreal, XR teams creating conversational characters for mixed reality training and social worlds, L&D and simulation builders running AI roleplay training for enterprise or education. Contact Sales pricing.
What's new in Convai
Checked 3 days agoAcross the latest 5 updates: 5 feature updates.
Custom Convai Actions in Unreal Engine: Build an AI Player That Picks Up and Places Objects (Part 2)
Second part of a tutorial on custom Convai Actions that let an AI player in Unreal Engine pick up and place objects in the scene.
Multiple AI Characters in One Unity Scene: How Convai Decides Who the Player Is Talking To (Part 1)
Convai explains the turn-taking logic it uses when several AI characters share one Unity scene with a single player.
Convai Scene Tagger: Tag an Entire Unreal Engine Level for AI Characters
Scene Tagger tags a full Unreal Engine level for AI characters in minutes, giving them environmental context at level scale.
Connect AI Characters to External Tools and Systems with MCP
MCP support lets Convai characters call external tools and systems at runtime rather than staying confined to the scene.
Convai Unity MCP: Build AI Characters in Unity with Codex, Claude Code, and Cursor
Unity MCP integration lets developers create and configure AI characters in Unity from Codex, Claude Code, or Cursor.
What people actually say about Convai — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
62 mentions across 6 sources (Hacker News, YouTube, Bluesky, Stack Overflow, GitHub, Lemmy) · researched Jul 23, 2026.
Average across the 6 sources that answered — each source counts once, not each post.
- +Real-time multimodal perception sees and hears environment for natural interactions.
- +Unity and Unreal Engine integrations enable easy plugin setup for developers.
- +No-code character creation from browser accessible for non-programmers.
- +Maya on Meta Quest 3 showcases impressive mixed reality AI avatar capabilities.
- +MCP integration allows analytics queries via Claude, Cursor, or Codex.
- −Pricing is opaque with no public tiers, frustrating budget-conscious developers.
- −Black camera issue on Apple Vision Pro remains unresolved.
- −Second Life community strongly opposes generative AI integration.
- −Small GitHub community with limited support and unresolved issues.
- −Stack Overflow presence is negligible with only one relevant post.
- • No public pricing; likely usage-based fees for API calls or cloud hosting that can escalate at scale
Viability Score
How well maintained and how widely used is Convai? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Real-time multimodal perception — characters see and hear their surroundings
- Human-like dialogue, voice, gestures, and contextually appropriate actions
- Spatial intelligence: characters understand and react to 3D environments
- No-code character creation in the browser with Avatar Studio
- Convai Sim for testing and prototyping character-driven scenarios
- Unity plugin for shipping conversational AI characters in games
- Unreal Engine plugin with AI players that talk, act, and read live game state
- Convai Scene Tagger for tagging an entire Unreal Engine level in minutes
- Convai Actions for scripting character behavior, including object pickup and placement
- Multi-character turn-taking logic in a shared Unity scene
- Dynamic Context for live game state and scene awareness in Unreal Engine
- Object in Attention: AI characters know what the player is looking at
- In-Context Knowledge Bank for multimodal knowledge grounding
- MCP support to connect AI characters to external tools and systems
- Unity MCP integration to build characters from Codex, Claude Code, and Cursor
About Convai
Convai is a conversational AI platform for building embodied 3D characters that perceive their surroundings and respond with voice, gestures, and actions. The company's stated premise is that humans understand the world through a body, so an AI that reads a scene and reacts to it lands differently than a chat window bolted onto a game. The build path runs in three moves — craft the character's mind, embody it in an avatar, then deploy into your own environment. Two groups get served. Creators work in Avatar Studio and Convai Sim, both no-code and browser-based, assembling roleplay avatars and spatial experiences without opening an engine. Developers get Unity and Unreal Engine plugins, a Web SDK with React Three Fiber and Three.js support, open APIs, and documentation for shipping those characters into live games and virtual worlds. The 2026 releases lean hard on the developer story. Convai Actions lets you script what characters actually do in Unity, and a September 2026 tutorial extends that to Unreal Engine with AI players that pick up and place objects. Convai Scene Tagger tags an entire Unreal Engine level for AI characters in minutes, and turn-taking logic now handles multiple AI characters sharing one Unity scene with a single player. The In-Context Knowledge Bank grounds characters in multimodal knowledge, MCP support connects them to external tools, and Unity MCP lets you build from Codex, Claude Code, or Cursor. An August 2026 push also covers industrial AI assistance for manufacturing training. Where it sits: general-purpose chatbot builders hand you a conversation and a text box; Convai hands you a character that knows what it's looking at and where it's standing. That specificity costs you — it's 3D-first, engine-centric work, sold to studios and enterprises rather than hobbyists. For a website help widget, this is both the wrong tool and a far more expensive one than you need.
Behind the Verdict
Convai's real differentiator is not the conversation layer — plenty of platforms do dialogue. It's the perception and action loop inside a 3D scene. Characters read game state through Dynamic Context, know what the player is looking at via Object in Attention, and can be told to act through Convai Actions. Scene Tagger removes the tedious part of that setup by tagging an entire Unreal Engine level for AI characters in minutes rather than level-by-level. Turn-taking logic for multiple AI characters in one Unity scene, documented in Convai's September 2026 tutorial, addresses the failure mode most multi-NPC demos hit: every character answering at once. Strengths: genuine engine-native plugins for Unity and Unreal Engine rather than a bolted-on REST call; a no-code on-ramp in Avatar Studio and Convai Sim so designers can prototype without engineering; multimodal perception covering sight and sound; the In-Context Knowledge Bank for grounding characters in your own material; and MCP support both for connecting characters to external tools and for building them from Codex, Claude Code, or Cursor via Unity MCP. Weaknesses: this is authoring work, not a switch you flip. Dynamic Context and Object in Attention surface game state, but someone has to wire them to something meaningful, and character quality depends on how well you write the mind, the knowledge base, and the context hooks. The platform assumes engine or Web SDK capacity on your side — there's no path here for a team with no Unity, Unreal, or Three.js/React Three Fiber skills. Convai's own August 2026 research write-ups on AI roleplay training and VR simulation frame outcomes as evidence-dependent, which is a fair signal that the platform amplifies good scenario design rather than substituting for it. Where it fits: game studios building NPCs that react to gaze, game state, and scene context; XR teams running mixed-reality training where an avatar has to roleplay a customer or patient; social VR worlds that want characters with memory and spatial awareness; manufacturing L&D programs that need expert knowledge at the point of work. Where it doesn't: text-only assistants, marketing-site chat widgets, and any project where perception and embodiment add nothing to the user's job.
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Real-world workflow fit
Concrete scenarios for the personas Convai actually fits — and what changes day-one when you adopt it.
You import the Convai Unity plugin, create a character in Avatar Studio, then wire Dynamic Context to your game state so the NPC comments on what just happened in the level. Turn-taking logic keeps two AI characters from both answering the player at once.
Outcome: A playable scene where NPCs respond to actual events rather than canned lines, built without standing up your own speech and reasoning pipeline.
You run Convai Scene Tagger over a full level so every prop and surface is tagged for AI characters in minutes, then use Convai Actions to let an AI player pick up and place objects during a scripted sequence.
Outcome: Characters that can reference and manipulate the environment instead of standing in place talking, with level tagging done in one pass rather than prop by prop.
You build a mixed reality roleplay simulation where an AI avatar plays a customer or patient, grounded in your own procedures through the In-Context Knowledge Bank, and test the scenario in Convai Sim before deploying to Meta Quest.
Outcome: Trainees rehearse against a character that adapts to what they say and do, with your internal knowledge behind the responses.
Use Cases
- Create lifelike NPCs that converse with players in Unreal Engine 5 games
- Build mixed reality training simulations where AI avatars roleplay customer or patient interactions
- Deploy a brand avatar on a website using pixel streaming to engage visitors in conversation
- Develop a virtual tour guide that sees and responds to user gestures in VR
- Enable social VR worlds with AI characters that remember past conversations and adapt
- Run an AI avatar in a browser using Unity WebGL for interactive web experiences
- Give manufacturing trainees an industrial AI assistant with expert knowledge at the point of work
- Script an Unreal AI player that reads live game state and picks up and places objects
Models Under the Hood
as of 2026-10-16
Limitations
- The platform is built around game-engine and web integration (Unity, Unreal Engine, Three.js/React Three Fiber, Unity WebGL, Meta Quest XR).
- No-code creation is offered through Avatar Studio and Convai Sim, but full use still involves engine plugins, MCP-based tooling, or open APIs.
- Expect real authoring work on the character's mind, its knowledge base, and its context hooks — Dynamic Context and Object in Attention surface game state, but you have to connect them to something meaningful, and turn-taking across multiple characters in one Unity scene needs deliberate setup.
- Convai's own August 2026 writing frames AI roleplay training and VR simulation value as evidence-dependent, a fair signal that outcomes rest on scenario design rather than the platform alone.
as of 2026-10-19
Verification history
We have re-verified Convai 22 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 22 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Convai tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Enterprise
Contact sales
Ideal for
Studios, XR teams, and enterprise L&D groups deploying AI characters into shipped games, VR training, or industrial workflows at scale.
What this tier adds
Starting and only published tier — custom pricing scoped to usage and deployment, bundling Unity and Unreal Engine plugins, the Web SDK, open APIs, and MCP support.
Where the pricing makes sense
The company stage and team size where Convai's pricing actually pencils out — and where peers do it cheaper.
Convai's pricing fits teams whose volume aligns with the published tiers. Compare against the alternatives listed below for stage-specific value.
Setup time & first value
How long it actually takes to get something useful out of Convai — broken out by persona, not the marketing-page minute.
A no-code avatar in Avatar Studio can be conversational within an afternoon. Budget days to a couple of weeks for the first engine-integrated character in Unity or Unreal, since Dynamic Context, Object in Attention, and Actions all need wiring to your game state before characters behave usefully.
Switching to or from Convai
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a general-purpose chatbot builder: rebuild the dialogue in Avatar Studio, then attach the character to a Unity or Unreal avatar so it inherits scene perception the old tool could not provide.
- →From a custom in-house NPC dialogue system: keep your animation and behavior layers and route dialogue through the Convai Unity or Unreal Engine plugin via the open APIs.
- →From scripted dialogue trees: replace branching nodes with the In-Context Knowledge Bank so characters answer off-script, then add Convai Actions for the behaviors the trees used to hardcode.
- ↗To a text-only chatbot platform: export your written character brief and knowledge material, since the spatial and gesture layers have no equivalent there.
- ↗To a custom build on raw model APIs: your prompts, knowledge documents, and scene-context definitions port over, but you rebuild speech, lip-sync, and engine hooks yourself.
Integrations
Resources & Guides
- Resourceconvai.com
How to Add Custom and Parameterized Actions to Convai AI NPCs in Unreal Engine 5: Phase 2 Guide
Helpful link from convai.com
- Resourceconvai.com
How to Build Convai-Powered AI NPC VR Projects in Unity for Meta Quest: Full Setup Guide
Helpful link from convai.com
- Resourceconvai.com
How to Set Up Hands-Free AI NPC Conversations in VR with Convai and Unreal Engine 5
Helpful link from convai.com
- Resourceconvai.com
Convai Analytics MCP: Query Your Session Telemetry with Claude, Cursor, Codex, or Any MCP Client
Helpful link from convai.com
- Resourceconvai.com
Meet Maya: Photorealistic 3D AI Avatar You Can Talk to in Mixed Reality on Meta Quest 3
Helpful link from convai.com
- Resourceconvai.com
How to Make AI NPCs Act on Your Commands in Unreal Engine 5 with Convai: Prompt-to-Action and Dynamic NPC Actions Guide
Helpful link from convai.com
- Resourceconvai.com
How To Build Mixed Reality Ai Characters In Unity With Convai On Meta Quest 2026
Helpful link from convai.com
- Resourceconvai.com
How To Use Dynamic Context In Convai To Build Ai Characters That React In Real Time
Helpful link from convai.com
Tutorials & Learning
YouTube returned 6 videos for “Convai”, and we withheld 6: 6 could not be judged, because “Convai” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Convai.
Official links
Tools that pair well with Convai
Common stack mates teams adopt alongside Convai, with the specific reason each pairing earns its keep.
Unity Mcp
Unity MCP by Coplay is an AI agent that completes Unity game development tasks inside the editor from plain-English prompts.
ComfyUI
ComfyUI is an open-source node-based engine for AI image, video, audio, and 3D generation with inspectable workflows.
Opus
Opus turns text prompts into playable 2D and 3D game worlds, with AI co-pilots and one-click export.
Featured Head-to-Head Comparisons
Convai vs Toolhouse
Choose Toolhouse if you need an autonomous AI worker to handle repetitive business tasks like email follow-ups, document processing, and lead qualification without coding. Choose Convai if you're building interactive 3D characters for games, XR, or brand experiences that need to see, hear, and react in real-time. They solve completely different problems.
Convai vs Notable
Notable and Convai serve entirely different markets: Notable automates healthcare workflows (patient access, RCM, care ops) for large health systems, while Convai builds lifelike 3D AI characters for games and XR. Your choice depends on domain — pick Notable if you are a healthcare enterprise seeking to reduce denials and staff workload; pick Convai if you need interactive NPCs with real-time perception for virtual worlds.
Convai vs Poke Interaction Co
Choose Poke if you need a personal AI assistant to manage email, calendar, and tasks from your chat apps, especially if you want proactive automations or real human help for errands. Choose Convai if you're building AI characters for games, XR, or brand experiences that need to see, hear, and interact in 3D spaces—their no-code tools and Unity/Unreal integrations make it easy. There's no overlap; your use case dictates the winner.
Alternatives to Convai
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Frequently Asked Questions
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