AI Platform · Legal Tech · RAG2026
AI discovery platform for criminal defense
Multi-tenant platform that turns criminal discovery (police reports, recordings, emails, subpoena returns) into a searchable, source-cited case record for defense attorneys.
2M+
pages of discovery ingested for a single defense team

- Client
- CrossLogic Intelligence
- Year
- 2026
- Type
- AI Platform · Legal Tech · RAG
What was the problem?
Defense attorneys receive discovery as thousands of unsorted files: police reports, bodycam and interview recordings, emails, bank and subpoena returns. A single federal case can run past 80,000 pages. Reading it by hand is slow and expensive, and a missed name or date can decide the outcome. CrossLogic's founders, former detectives and forensic examiners, needed a platform that reads every file, builds the timeline and the cast of people, and answers questions with a citation back to the source.
What did I build?
- Ingest
- Parse and transcribe
- Extract
- Answer with citations
- Meter AI cost
- 1Ingests from browser upload or directly from Box, Dropbox and Google Drive, with parallel import lanes and duplicate detection.
- 2Parses and OCRs documents and emails, and transcribes bodycam, interview and audio recordings onto the same case record.
- 3Extracts people, organizations, locations and dated events, then merges them into one case-wide timeline and entity graph.
- 4Answers questions through hybrid retrieval (pgvector plus a keyword index), with every answer citing the document it came from.
- 5Meters AI cost per case and per stage, with per-case budgets and model routing set from an admin panel.
What was the result?
- An 83,000-page federal case fully extracted at about $0.003 per page in AI cost.
- Single Box imports of 110,000+ files, with duplicates caught before they cost anything.
- AI spend metered per case and stage, reconciling with the provider's bill to the cent.
What is it built with?
- FastAPI
- Next.js
- PostgreSQL + pgvector
- Celery + Redis
- OpenRouter (multi-model)
- Docker
- legal tech
- rag
- ai extraction
- multi-tenant saas