WellnessIQ (Naive vs Correlated Coaching)
Naive advice vs. correlated coaching — see the difference a real health picture makes.
WellnessIQ shows the same wellness question answered two ways — a naive, single-metric response and a correlated one that reasons across someone's full health picture — so the value of correlated coaching is visible, not just described.
Without a demo like this, the difference between shallow and genuinely personalized wellness guidance is hard to explain in the abstract.
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.
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 Strands, 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.