Chat with Company Documents, Spreadsheets & SQL Databases
Sub-50ms Hybrid Vector Search via LlamaIndex, Pinecone & Qdrant with Zero Hallucination
Transform petabytes of confidential enterprise PDFs, spreadsheets, databases, and code repositories into verified, instant intelligence with mathematically guaranteed citation provenance.
Multi-Stage Hybrid Retrieval Pipeline
Simple naive vector search fails in enterprise environments. We build multi-stage retrieval pipelines combining dense neural embeddings, BM25 keyword matching, and cross-encoder re-ranking.
Semantic Chunking & Metadata Tagging
Documents are parsed with layout-aware chunking (preserving tables, headers, and code blocks) and enriched with role-based access metadata.
Hybrid Indexing (Dense + Sparse)
Combines high-dimensional dense vector embeddings (BGE, Cohere) with sparse lexical inverted indexes (BM25) for exact keyword and acronym precision.
Cross-Encoder Re-Ranking
Top 50 retrieved candidate chunks pass through a deep cross-encoder re-ranker to score contextual relevance against the exact query intent.
Grounded Generation & Citation Auditing
The LLM generates answers strictly grounded in retrieved passages, outputting exact clickable page and paragraph citations.
Enterprise-Grade RAG Engineering
Designed to solve the hallucination, security, and scale challenges of large corporate knowledge bases.
Role-Based Access Control (RBAC)
Guarantees employees only receive answers based on documents they have active clearance to view in Active Directory or Okta.
- Pre-filtering queries by user permissions and security clearance
- Zero cross-departmental data leakage between HR, Finance, and R&D
- Seamless SAML, OAuth, and SCIM directory synchronization
Table & Unstructured Document Intelligence
Extracts insights from complex multi-page financial statements, SEC filings, CAD schematics, and medical reports.
- Specialized table-aware OCR and bounding-box preservation
- Semantic SQL conversion for structured tabular query execution
- High-resolution visual embeddings for charts and diagrams
Automated Hallucination & Drift Monitoring
Continuous evaluation suites verify that model outputs remain faithful to source texts across thousands of daily queries.
- Ragas and TruLens automated faithfulness scoring
- Real-time flagging of ungrounded or speculative statements
- Proactive vector index re-indexing on document updates
RAG & Vector Database Infrastructure
Qdrant / Pinecone
Vector DatabaseSub-millisecond dense and sparse vector indexing.
Cohere Rerank
Re-Ranking EngineState-of-the-art contextual cross-encoder ranking.
BGE / OpenAI Embeddings
Dense EmbeddingsHigh-dimensional semantic vector representations.
LlamaIndex
RAG OrchestrationAdvanced chunking, recursive retrieval, and query engines.
Unstructured.io
Document ParsingDeep extraction of complex PDFs, DOCX, and tables.
OpenTelemetry / LangSmith
ObservabilityEnd-to-end tracing of retrieval latency and token spend.
Technical & Engagement FAQs
Ready to Build Production AI That Actually Delivers ROI?
Schedule a 30-minute architecture session with our senior AI engineers. We'll assess your dataset, evaluate model feasibility, and draft an end-to-end implementation roadmap.