Concepts

How Heisenberg Works

Heisenberg 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

  • 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

Step 1

Ingest

Autonomous data agents continuously collect from Polymarket, Kalshi, social platforms, and on-chain sources via WebSocket and polling connections.

Step 2

Normalize

Raw data is cleaned, deduplicated, and transformed into a unified schema. Different platform formats become one consistent structure.

Step 3

Enrich

Data agents compute proprietary metrics — H-Scores, wallet profiles, market quality assessments, anomaly detection — on every update cycle.

Step 4

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 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.

Explore Further