LiveVoice
Talk to the model directly — real-time, full-duplex voice, no push-to-talk.
LiveVoice is a real-time voice conversation, not a record-then-transcribe flow — speak naturally and the model listens and replies in the same open audio stream, including interrupting it mid-sentence the way a real phone call works. Choose a locally-hosted voice model or Gemini's live voice API as the engine underneath the same interface.
Without it, a voice interface here means speak, wait, get a reply, speak again — the stop-and-go rhythm of a walkie-talkie, not a conversation.
This isn’t a proof of concept.
What you’re about to see is a fully containerized, production/enterprise-grade solution — the same build that deploys to Kubernetes on any of the three major cloud providers: AWS, Azure, or Google Cloud. There is no gap between this demo and what ships to production.
Built in, not bolted on
Observability — SSE, Phoenix & Live Logging
Every step streams live to the screen as it happens and mirrors into a self-hosted Phoenix tracing dashboard, exactly like the platform's production solutions.
Bring Your Own Model (BYOM)
Switch the underlying model with one setting — a fully local, on-prem model, GPT, Gemini, Claude, Amazon Bedrock, or Microsoft Foundry — with no code change.
Built as a Comparison, Not a Guarded Production Agent
This one is intentionally a side-by-side teaching demo, so it skips the enterprise governance/PII/prompt-injection layer that wraps the platform's production solutions — every other solution on this page carries that full layer.
Role-Based Access Control
Every account carries a role — user, admin or owner — and the server checks it before a solution opens, so a correct password alone isn't enough. Your username and role sit beside Log out, and every run starts with “Applying RBAC based access control” in the live stream.
What it’s built with
Python backend, served with Uvicorn
A FastAPI service running on Uvicorn handles every request — the same production Asynchronous Server Gateway Interface (ASGI) stack used across the whole platform, not a notebook or a prototype script.
FastMCP tool server — MCP v2 support
Database access, document tools and integrations are exposed through the Model Context Protocol via a dedicated FastMCP server running on MCP v2, so agents call real, typed tools instead of hand-rolled function stubs.
Large MCP Payload Support
We go beyond the default MCP payload of 5MB. We support MCP payloads of 5MB+.
Next.js frontend
A React/Next.js interface talks to the backend over Server-Sent Events for live streaming — no page reloads, no polling.
Choice of multi-agent framework
The same solution can run on LangGraph, Google ADK, or Microsoft Agent Framework — switchable per deployment, not hard-wired to one vendor's orchestration engine.
Agent2Agent (A2A) protocol support
Every agent pipeline also exposes a standards-based Agent-to-Agent (A2A) endpoint with a real, discoverable agent card — so another agent system can call it directly, not just this UI, including mid-conversation clarification round-trips.