I got tired of expensive SaaS tools that want my sensitive documents in their cloud. I built ArkhamMirror to do forensic document analysis 100% locally, free and open source.
What makes this different:
Air-gapped: Zero cloud dependencies. Uses local LLMs via LM Studio (Qwen, etc.)
ACH Methodology: Implements the CIA's "Analysis of Competing Hypotheses" technique which forces you to look for evidence that disproves your theories instead of confirming them
Corpus Integration: Import evidence directly from your documents with source links
Sensitivity Analysis: Shows which evidence is critical, so if it's wrong, would your conclusion change?
The ACH feature just dropped with an 8-step guided workflow, AI assistance at every stage, and PDF/Markdown/JSON export with AI disclosure flags. It's better than what any given 3-lettered agency uses.
Tech stack: Python/Reflex (React frontend), PostgreSQL, Qdrant (vectors), Redis (job queue), PaddleOCR, Spacy NER, BGE-M3 embeddings.
All MIT licensed. Happy to answer questions about the methodology or implementation! Intelligence for anyone.
Links:
Repo
https://github.com/mantisfury/ArkhamMirror
ACH guide with screenshots at
https://github.com/mantisfury/ArkhamMirror/blob/reflex-dev/d...