Synthetaic

RAIC Labs offers RAIC, an imagery search and discovery platform for finding specific objects and patterns across very large collections of satellite, aerial and other sensor imagery. The company positions it as intelligent imagery exploitation, summed up as making every pixel searchable. Instead of the usual cycle of collecting data, labeling it, training a model and running inference, RAIC detects or tiles imagery, encodes the results into a purpose built embedding space, and then reuses that representation for search, clustering, categorization, detection and monitoring on ordinary CPUs. The analyst loop starts from a single reference image, with no labeled training set, then searches a chosen area and time range, groups results by visual similarity, commits validated detections to a shared taxonomy and reseeds the search to tighten precision. Categories can be exported to CVAT 1.1 or GeoJSON. Analysts can also build shallow detectors from approved taxonomy categories, versioned and exported with class, confidence, location and source metadata. RAIC deploys as containerized services on Kubernetes across cloud, on premises, classified and fully air gapped environments. It integrates through REST APIs, STAC endpoints and GeoJSON, and an MCP server exposes search, taxonomy and detector operations to AI agents. The audiences are defense and intelligence teams, public safety and municipal agencies, and commercial geospatial teams. Pricing is not published. The site invites visitors to contact the company to evaluate RAIC against their own data and requirements.