RAG Development Service
Connect Large Language Models to your enterprise knowledge base with Advanced Retrieval-Augmented Generation (RAG). Eliminate hallucinations with hybrid search and vector databases.
Hybrid Keyword & Vector Search (HNSW
Cohere & Cross-Encoder Re-Ranking
Multi-Query & Contextual Compression
Automated RAG Evaluation (Ragas Framework)
Advanced RAG Architecture Systems
Simple vector search isn't enough for production enterprise AI. We build Advanced RAG systems featuring parent-child chunking, metadata filtering, semantic re-ranking, and agentic retrieval routing to ensure exact factual accuracy.
RAG Engineering Solutions
Vector Database Setup
Configuring Pinecone, Qdrant, Milvus, or PGVector for high throughput.
Smart Chunking
Semantic, hierarchical, and Markdown-aware document splitting.
Hybrid Search
Combining BM25 full-text keyword search with dense vector embeddings.
Semantic Re-Ranking
Using Cohere and BGE rerankers to surface top relevant context chunks.
GraphRAG Systems
Integrating Knowledge Graphs (Neo4j) for complex multi-hop reasoning.
Multimodal RAG
Parsing text, complex tables, charts, and images from enterprise PDFs.
Access Control (RBAC)
Filtering retrieval results based on individual user document permissions.
RAG Evaluation
Continuous monitoring of faithfulness, answer relevance, and context recall.
How RAG Works
Document Ingestion
Parsing unstructured files into vector embeddings.
Hybrid Querying
Retrieving top matching chunks via dense and sparse search.
Re-Ranking
Filtering top relevant snippets before sending to the LLM.
Grounded Answer
LLM generates answer with exact document source citations.
RAG Databases & Frameworks
Enterprise RAG Deployments
Internal Knowledge Search
Instant search across all company SOPs, wikis, and Slack threads.
Customer Support Bots
Accurate support agents that cite live user manual documentation.
Legal Discovery
Instant clause lookup across tens of thousands of legal contracts.
Frequently Asked Questions
Eliminate LLM Hallucinations With RAG
Talk to our vector search and RAG experts today.
Build Your RAG Engine