OXELVO
OXELVO
HYBRID VECTOR RAGFinancial Services & Regulatory Advisory•Production Blueprint & Benchmark

High-Throughput Regulatory & Compliance RAG Search Engine

A hybrid retrieval augmented generation search engine querying over 4,000,000 regulatory legal tokens with sub-second streaming responses, citation verification guardrails, and semantic query caching.

CORE STACK:pgvectorQdrantNext.jsFastAPICohereRedisDocker
High-Throughput Regulatory & Compliance RAG Search Engine Architectural Demonstration
HYBRID VECTOR RAG • PRODUCTION PROTOTYPE
The Technical & Operational Challenge

Identifying the Core Problem

Compliance officers and legal advisors spend hours cross-referencing multi-jurisdictional financial regulations. Standard search tools either miss semantic nuance (keyword only) or risk hallucinated clause citations (generic consumer LLMs).

Engineered Architecture & Solution

How OXELVO Solved It

We designed a hybrid vector pipeline pairing dense semantic embeddings (Qdrant) with sparse BM25 keyword indices, combined via Reciprocal Rank Fusion (RRF). A cross-encoder reranking model scores the top candidate chunks before prompt assembly, guaranteeing accurate clause citations.

Delivered Capabilities

Key System Features

  • Hybrid dense + BM25 sparse vector index with automated document diff synchronization
  • Cross-encoder reranking layer filtering irrelevant legal clauses
  • Redis semantic cache resolving repeated queries in under 15ms
  • Clean search interface embeddable directly into client intranet portals
  • Automated evaluation harness testing precision and recall against legal gold standards
Architectural Blueprint Highlights

Engineering Decisions & Guardrails

Zero customer data retention agreement with embedding endpoints
Sub-20ms vector cosine similarity lookups over 4M chunk vectors
Deterministic citation guardrails stripping any unverified reference
Project Transparency Notice

This project represents an active technical demonstration and architectural blueprint engineered by OXELVO. We share code blueprints, schemas, and live demonstrations to verify real-world feasibility before client commercialization.

SPECIFICATIONSVERIFIED
Search ModeHybridDense Qdrant + BM25 sparse fusion
Target Latency< 180msP95 streaming inference response
Citation GuardrailDeterministicStrict verification against source tokens
Cache LayerRedisSemantic similarity query caching
TIMELINE:4 Weeks Sprint
STATUS:Production Blueprint & Benchmark
SIMILAR CHALLENGE?

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