Mireye: Infrastructure for Physical World AI Agents
Building the data backbone for AI agents to understand real-world locations.
1The Physical Data Gap in AI
Mireye addresses a critical gap where AI agents excel at digital reasoning but lack understanding of physical locations. Founder Ansh discovered this while building construction agents and through conversations with Fortune 500 insurers. Current models often hallucinate when asked location-specific questions, creating unreliable outputs for real-world applications.
2From Niche App to Infrastructure
Initially launched as a site-screening application, Mireye pivoted when users showed more interest in the underlying engine than the app itself. Data showed 311 of 317 catalog fields were being queried with no dominant use case. This led to building comprehensive infrastructure rather than a single-purpose application.
3Beyond Basic Data APIs
Mireye provides more than just datasets - it offers enriched data (owner info, acreage, structures), specialized tools (geometry calculations, parcel resolution), and change signals (like rezoning notices). The system returns data with explicit typing: 'ok', 'absent', or 'failed' to prevent AI misinterpretation of null values.
4Learning from Agent Failures
The platform's tools emerged from observing real agent failures: eyeballing distances instead of calculating, selecting wrong parcels, or budget overruns. Mireye now packages complete workflows like site screening or address underwriting, with deterministic tools that prevent common agent mistakes.
5The Data Normalization Challenge
Aggregating location data requires county-by-county collection in various formats, then normalization into a unified schema. Mireye currently maintains 366 fields, each with specific contracts about sources, meanings, and refresh rates. Some data required public records requests, like unmapped sewer mains in North Carolina.
6On-Demand Indexing Innovation
Mireye's newest feature allows users to request unindexed fields. A long-running agent then researches sources, collects data, tests against ground truth, and indexes it - typically within a day. This creates an expanding knowledge base driven by real user needs.
7Diverse Industry Applications
Users have applied Mireye in unexpected ways: insurers screening for natural disasters, proptech cleaning address data, wellness brands selecting ad locations, robotics companies sourcing warehouses, and even human trafficking investigations. The platform's flexibility supports diverse physical world decisions.
8The Future of Physical Data
Mireye's mission to make every inch of earth as queryable as the web represents a fundamental infrastructure layer for spatial AI. With transparent pricing starting at 5,000 free monthly credits, it lowers barriers for developers building location-aware agents while maintaining data reliability through rigorous sourcing and typing.
Original article: Hacker News: Launches — Mireye: Infrastructure for Physical World AI Agents