Enterprise RAG & Vector Knowledge Search
Connect large language models to your real-time corporate documents, databases, and APIs. We build enterprise RAG pipelines with sub-second vector retrieval and 100% verified source citations.
Grounded AI Intelligence with Verifiable Source Citations
Generic AI models hallucinate when asked about proprietary business information. BigIntend’s advanced Retrieval-Augmented Generation (RAG) architectures ingest your PDFs, contracts, wikis, and SQL tables into lightning-fast vector stores, delivering precise, citation-backed answers in real-time.
Zero Hallucinations
Responses strictly grounded in your verified corporate documentation.
Sub-500ms Queries
Optimized HNSW vector indexing for instant multi-million document search.
Role-Based Access (RBAC)
Dynamic document ACLs ensure users only see data they are permitted to view.
Our Enterprise RAG Engineering Capabilities
Intelligent Document Parsing & Chunking
Multi-modal extraction from complex tables, scanned PDFs, PPTs, spreadsheets, and hierarchical markdown documents.
- Semantic & Context-Aware Chunking
- OCR & Multi-Column Table Parsing
Vector Database Architecture & Indexing
Production setup of high-performance vector databases with metadata filtering and partitioned enterprise indexing.
- Pinecone, Qdrant & Milvus Deployment
- HNSW & IVF-Flat Index Optimization
Hybrid Dense + BM25 Lexical Search
Combine keyword exact-match precision with dense semantic vector embeddings to ensure technical terminology is never missed.
- Reciprocal Rank Fusion (RRF)
- Sparse + Dense Vector Hybrid Queries
Cross-Encoder & Cohere Re-Ranking
Two-stage retrieval pipelines that filter and score top-k chunks using state-of-the-art neural cross-encoders for maximum precision.
- Cohere Rerank 3 Integration
- ColBERT Token-Level Scoring
Dynamic ACLs & Enterprise RBAC
Enforce strict user permissions and document confidentiality at retrieval time without re-indexing your entire database.
- Active Directory / Okta Sync
- Metadata-Level Permission Filtering
RAG Triad Evaluation & Monitoring
Automated benchmarking of Context Relevance, Groundedness, and Answer Relevance using Ragas and TruLens telemetry.
- Continuous Retrieval Drift Alerts
- Automated Golden Dataset Regression Testing
RAG Technologies & Vector Infrastructure
Our 5-Step RAG Engineering Lifecycle
Corpus Ingestion & Data Hygiene
We catalog unstructured documents, identify PII, and design structured metadata schemas.
Chunking Strategy & Vector Indexing
We test semantic vs recursive chunking and generate high-dimensional vector embeddings.
Hybrid Retrieval & Re-ranking Tuning
We optimize BM25 + dense weights and integrate cross-encoder re-ranking models.
Security Guardrails & RBAC Enforcement
We bind retrieval to your identity provider to enforce granular user-level permissions.
Production Deployment & RAG Telemetry
We deploy low-latency endpoints with automated hallucination tracking and drift alerts.
Frequently Asked Questions
Build Custom Enterprise RAG
Turn your organization's scattered documents into a lightning-fast intelligent knowledge engine.