CASE 07LegalTech & Capital Markets · Apex Legal & Capital
Enterprise Document Intelligence & RAG Knowledge Engine
Automated semantic extraction, audit validation, and search for 500,000+ legal & financial contracts
Performance Impact
+90%
Business Growth
+90%
Time to Production
8 weeks
AIVERIFIED PRODUCTION
The Legacy Challenge
What the client was facing
Legal associates spending thousands of manual hours reviewing 80-page credit agreements and merger contracts to verify regulatory clauses and compliance covenants.
Architectural Solution
What NemeaForge Engineered
Engineered a private cloud RAG architecture using Qdrant vector database, LangChain/LlamaIndex pipelines, and custom fine-tuned embeddings with strict tenant data isolation.
Key System Highlights
- Hybrid semantic retrieval combining dense embeddings with BM25 keyword matching
- Table-aware OCR ingestion parsing complex financial tables into structured JSON
- Strict citation validation engine ensuring all model responses link directly to source page/paragraph
- Tenant-isolated vector collections ensuring complete confidentiality between client matters
Measurable Outcomes
Business & Technical Impact
- Contract review time reduced from 5 hours to under 30 minutes (90% reduction)
- 99.2% extraction accuracy validated across 50,000 test contract clauses
- $1.8M in billable associate hours redirected toward high-value strategic counsel
Technologies Utilized
PythonLangChainQdrantOpenAI / GeminiFastAPINext.jsPostgreSQLDocker
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