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TruGen conversational video pipeline — WebRTC capture, STT, Hawkeye-1 vision, LLM, TTS, Huma-2 render
TruGen is a platform for building real-time AI video teammates — agents that hold live, face-to-face conversations with your users through a photorealistic avatar. A teammate sees the user through their camera, hears them through their microphone, and answers with lip-synced speech in under a second — grounded in your data, wired to your tools, and speaking whichever of 60+ languages the user chose. Underneath: TruGen’s proprietary Huma avatar renderer, the Hawkeye vision model, a fully pluggable STT → LLM → TTS pipeline, and enterprise-ready primitives for auth, sessions, and compliance. Ship with a single iFrame, a drop-in React widget, or the JavaScript / Python SDK — every path runs on the same infrastructure underneath.

What you can build

Customer support agents

Handle inbound questions with brand-accurate answers grounded in your docs.

Sales & lead qualification

Qualify inbound leads, demo products, and hand off to a human when the conversation calls for it.

Interviewers & assessors

Run structured interviews, score responses, and produce transcripts you can review.

Onboarding & training

Walk new hires or customers through a guided flow with vision-aware coaching.

Healthcare intake

Collect symptoms, history, and consent before the appointment — in the patient’s own language.

Language & skills tutors

Practice, correct, and coach with a patient teacher that never runs out of hours.

Financial concierges

Guide users through applications, KYC, and product selection with a calm, compliant voice.

In-store & kiosk agents

Turn any screen with a camera into a helpful teammate that greets and assists customers.
Anywhere a human once had to have a conversation, an agent can. See real-world examples →

How it works

Every agent runs through the same five-stage pipeline. Each stage is pluggable, and every stage can be configured per agent.
1

Capture — WebRTC in

The user’s audio and video stream into the pipeline with sub-100 ms transport, from any modern browser or mobile web.
2

Perceive — STT + Hawkeye-1

Speech-to-text transcribes audio in real time. Hawkeye-1 analyses the video stream for gaze, gesture, and scene context — and hands both to the LLM.
3

Reason — LLM

The language model generates a response using the agent’s system prompt, attached knowledge base, memory, and available tools.
4

Speak — TTS

Text-to-speech renders the response as natural, expressive audio in the language the user spoke.
5

Render — Huma-2 + WebRTC out

Huma-2 generates the avatar video frame-by-frame, synced to the audio, and streams both back to the user — closing the loop in under a second.
Read the full pipeline breakdown →

Performance characteristics

Numbers are measured on the default Groq + ElevenLabs stack. Latency and quality vary with your chosen LLM, TTS, and network path.

Foundation models

TruGen ships three proprietary models. Each has a specific job — combine them or use them independently. Compare models in depth →

Three ways to build

No-code — Studio

Create, configure, and test an agent in the TruGen Studio. Ship with an iFrame in a single line.

Low-code — Widget

Drop the React widget into any app with an agentId. Full theming, no WebRTC handling.

Full-code — SDKs

Use the JavaScript or Python SDK for custom UIs, custom event pipelines, or server-driven agent orchestration.

Next steps

Quickstart

Create your first agent and embed it in under 5 minutes.

Agent concepts

Understand what an agent is, how conversations flow, and what’s configurable.