{"slug": "launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents", "title": "Launch HN: Mireye (YC S26) – Infrastructure for Physical World AI Agents", "summary": "Mireye (YC S26) launched an API infrastructure that connects AI agents to cited physical-world data, enrichment, tools, and signals, enabling them to answer location-based questions with sources, timestamps, and confidence scores. The service targets sectors such as data center siting, renewable energy, insurance underwriting, and mortgage/title, and includes features like geocoding, lookup, fetch, proximity, and a field-request system that queues builds for missing data.", "body_md": "# Physical world context for AI agents\n\nOne API for data, enrichment, tools and signals.\n\n## Every value cited\n\n## Power your agents to make decisions about the physical world\n\nWhat's the elevation at 40.7128, -74.006?\n\nI don't have real-time access to elevation databases. Based on general knowledge, the area near 40.7128, -74.006 (Manhattan, NYC) has elevations ranging from roughly sea level to about 10 to 50 meters depending on the specific location.Would you like me to suggest some online tools for looking up precise elevation?\n\nNo source. No timestamp. Estimated range.\n\nWhat's the elevation at 40.7128, -74.006?\n\nThe elevation at 40.7128, -74.006 is 13.03 meters above sea level (NAVD88 datum).\n\n- elevation\n- = 13.03 meters\n- source\n- =\n[USGS_3DEP_COG](https://www.usgs.gov/3d-elevation-program) - fetched\n- = 2026-07-28\n- confidence\n- = medium\n\nFederal source, clickable URL, fetched timestamp, confidence.\n\n## One API to connect your agents to physical world data, enrichment, tools and signals\n\nAI agents — Claude, ChatGPT, Kimi, Gemini, Cursor, Grok, Copilot, DeepSeek, or custom agents — ask Mireye through one API with MCP tools. Mireye returns cited data, enrichment, proprietary fields, signals and tools, indexed from the physical world. A field the catalog doesn't have yet can be requested — matched against the catalog first, and a genuine gap becomes one queued build that flows back into Mireye for every caller after.\n\n## Sectors we power\n\nEvery “should I care about this place, and why?” question routes to the same API — these are the desks already asking it.\n\n### Data center siting\n\n### Renewable energy siting\n\n### Insurance underwriting\n\n### Mortgage & title\n\n### Residential land\n\n### Commercial lending\n\n## Ask anything about a place.\n\nAsk a question about a place and get a cited answer. One call can resolve an address, fetch fields, and measure distances, and you get back the plan it ran so you can replay it.\n\nmireye powered agent · claude-opus\n\n## Turn anything into a place.\n\nSend a US street address and get back the coordinate it names, with how that coordinate was derived — sitting on the parcel, or interpolated along a street centerline — and a confidence score. Centroid-grade and low-confidence matches are refused rather than guessed.\n\nmireye powered agent · gpt-5 · tools: mireye_geocode\n\n## One string, the whole stack.\n\nGeocoding gives you a point. Lookup gives you the place: county, tract, congressional district, metro, timezone, elevation and flood status resolved in the same call — and a typed refusal when the match is not good enough to stand behind.\n\nmireye powered agent · gpt-5 · tools: mireye_lookup\n\n## Cited facts at any location.\n\nName the fields or a preset and get typed values for any US location, each with its source, fetch time, and confidence. Send hundreds of locations in one call, and one bad address does not fail the rest.\n\nmireye powered agent · claude-opus · tools: mireye_fetch\n\n## Measure what the data can't say.\n\nFour drive-time operations at any US or Canadian location: point-to-point distance, nearest-by-road over curated infrastructure sets — airports, substations, power plants, rail, ports, urban areas — screening by drive-time cutoff, and labor sheds. Every answer states what it charged and what it can't know.\n\nmireye powered agent · gpt-5 · tools: mireye_proximity\n\n## Request a field that doesn't exist yet.\n\nDescribe the data in plain language, with the locations where you need it. Already in the catalog and you get the field plus a cited sample now; close but not exact and you get the near miss to accept or reject; nothing answers it and one build is queued with a request_id to poll. An ask Mireye can't index — real-time, commercially licensed, personal contact data — comes back as a typed no with somewhere else to go.\n\nmireye powered agent · gpt-5 · tools: mireye_request_field, mireye_field_request_status", "url": "https://wpnews.pro/news/launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents", "canonical_source": "https://www.mireye.com", "published_at": "2026-09-03 16:24:13+00:00", "updated_at": "2026-09-03 16:54:47.539933+00:00", "lang": "en", "topics": ["ai-infrastructure", "ai-tools", "ai-agents", "developer-tools"], "entities": ["Mireye", "YC S26", "USGS 3DEP", "Claude", "ChatGPT", "Kimi", "Gemini", "Cursor"], "alternates": {"html": "https://wpnews.pro/news/launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents", "markdown": "https://wpnews.pro/news/launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents.md", "text": "https://wpnews.pro/news/launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents.txt", "jsonld": "https://wpnews.pro/news/launch-hn-mireye-yc-s26-infrastructure-for-physical-world-ai-agents.jsonld"}}