ContextFormers
ContextFormers provides a multi-modal AI extraction platform that turns unstructured video, photos, documents, 360° panoramas, and LiDAR data into validated, searchable structured data. The platform connects extracted signals to organization-specific people, assets, and terminology, with deployment options including air-gapped environments for privacy-sensitive work. It operates across three product lines: Media Intelligence for broadcast archives, Facility Intelligence for indoor asset mapping, and Infrastructure Intelligence for utility network digitization.
- Artificial Intelligence
- Data & Analytics
- Utilities
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Organizations with large archives of unstructured visual data—video, photos, documents, 360° scans, and LiDAR—struggle to extract actionable intelligence from them. Manual analysis is slow, expensive, and often skipped entirely, while generic cloud AI platforms fail to recognize organization-specific people, assets, or terminology and raise privacy concerns by processing sensitive content on external servers.
Solution
ContextFormers provides a multi-modal AI extraction platform that ingests diverse source material—video, photos, documents, 360° panoramas, and LiDAR—and turns it into validated, searchable, structured data. The platform uses a consistent five-stage engine: ingest, extract, form context, validate, and deliver. Extracted signals are connected to the customer's own people, assets, places, terminology, and relationships, then validated through confidence scoring, evidence comparison, and optional human review. The output is delivered directly into existing systems such as search, GIS, asset management platforms, and APIs. The system runs across three product lines: Media Intelligence for broadcast archives, Facility Intelligence for indoor asset mapping, and Infrastructure Intelligence for utility network digitization.
Target Audience
Primary users include broadcast archivists and media licensing teams managing large video collections, as well as clinical engineering managers, facility operations managers, and ADA compliance officers overseeing hospitals, campuses, and commercial buildings. The infrastructure product serves GIS managers and network engineers at electric, gas, water, wastewater, and telecom utilities.
Features
- Patent-pending fusion engine that weighs face identity, visual semantics, spoken word, and on-screen text into a single relevance score for multi-modal search
- Operator-defined identity registry that lets users register organization-specific subjects (e.g., "the defense attorney in the Smith trial") rather than relying on generic celebrity models
- Frame-level precision search that returns exact frames, not just video titles or timestamp ranges
- Multi-view AI detection for 360° panoramas with simultaneous LiDAR scanning, enabling X, Y, Z coordinate placement on floor plans
- Multi-modal cross-verification combining object recognition, spatial reasoning, and OCR text context for high-confidence asset categorization
- Human-in-the-loop training for infrastructure drawings that learns each utility's nonstandard legacy symbol sets
- Geospatial alignment engine that transforms local plan-sheet coordinates into sub-meter-accurate GIS positions
- Network validation that flags dangling laterals, orphaned assets, false loops, and connectivity gaps against source GIS
- Privacy-safe processing with tenant isolation, automated PII redaction, and on-premises or air-gapped deployment options
- Auto-generation of ArcGIS Indoors feature layers and GeoJSON exports with rich attribution