How Heisenberg AI Works
Heisenberg AI is an intelligence execution layer for prediction markets. It connects to live data sources, enriches everything through autonomous data agents, and serves it all through a single, sub-300ms API.
The Problem
- ×Data fragmented across Polymarket, Kalshi, social platforms
- ×Each platform has its own API, auth, rate limits, and format
- ×No computed analytics — just raw data you have to process yourself
- ×Building takes weeks of integration work per platform
With Heisenberg AI
- ✓One endpoint, all platforms, unified format
- ✓Sub-300ms latency, seconds-fresh data
- ✓Proprietary analytics: H-Score, Wallet 360, Market 360
- ✓Start building in minutes, not weeks
Architecture
Ingest
Autonomous data agents continuously collect from Polymarket, Kalshi, social platforms, and on-chain sources via WebSocket and polling connections.
Normalize
Raw data is cleaned, deduplicated, and transformed into a unified schema. Different platform formats become one consistent structure.
Enrich
Data agents compute proprietary metrics — H-Scores, wallet profiles, market quality assessments, anomaly detection — on every update cycle.
Serve
Enriched intelligence is served through the unified API with sub-300ms latency. Query any metric, any platform, with a single POST call.
Core Principle
Heisenberg AI is an execution layer, not a static data warehouse. Data agents connect to live sources continuously — so you always get the freshest results, enriched with proprietary intelligence, delivered in under 300 milliseconds.