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Vima turns egocentric construction footage into auditable spatial evidence. Instead of asking a model to guess from raw video, Vima builds a compact evidence layer first, then exposes it to humans and agents through a dashboard, HTTP API, CLI, and MCP server.

Evidence First

Frames are grounded with cached CII labels, zone attribution, and spatial context before they become an answer.

Agent Native

MCP and CLI interfaces let external agents inspect the same production evidence as the dashboard.

Small Production Footprint

Expensive perception is precomputed offline, so the hosted services stay light enough for a 1 vCPU / 2 GB VPS.

Auditable Outputs

Tool responses are structured JSON with frame rows, zone metrics, and temporal evidence instead of ungrounded prose.

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Production Surfaces

SurfaceURL
Landinghttps://vimaspatial.tech
APIhttps://vimaspatial.tech/api
MCPhttps://vimaspatial.tech/mcp
MCP Healthhttps://vimaspatial.tech/mcp/health

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Pipeline

Hardhat frames
  -> precomputed spatial inference
  -> CII work labels
  -> COLMAP zone attribution
  -> cited dashboard / API / agent response

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Current Hosted Facts

  • 30 sampled masonry frames
  • 86.7% wrench time
  • Cached CII frame rows and spatial zones
  • Offline inference artifacts served through a small hosted API
The hosted MCP route depends on the main Vima app deployment. If /mcp/health returns 404, the docs are deployed but the main app has not shipped the MCP service yet.