Rank #752 · on radar since 2026-07-03
Veridoc
A fully local, privacy-preserving RAG pipeline optimized for reasoning over dense financial documents. Veridoc uses LLMLingua-2 for token-level context compression and local LLMs to solve the "lost in the middle" problem—enabling multi-hop reasoning on SEC filings without external cloud APIs.
Visit homepage ↗llmrag-chatbotoptimisationaiml+3
Momentum
42.2
24h–7d–
Why it's ranked
Every score decomposes into published factors — the same math for every tool, paid or not. Read the methodology →
| Velocity (weighted, cohort-normalized) | 0.438 |
| Signal decay | 0.995 |
| Corroboration | 1.000 |
| Quality gate | 1.000 |
Raw signals (30 days)
github · forks0 latest · 2 snapshots
github · stars1 latest · 2 snapshots