RAG & Knowledge Agent Development
Build AI agents grounded in your proprietary data. Retrieval-Augmented Generation systems that deliver accurate, hallucination-free responses from your documents, databases, and knowledge bases.
What is RAG & Knowledge Agents?
Retrieval-Augmented Generation (RAG) is the technique of grounding AI responses in your actual data rather than relying solely on an LLM's training data. RAG agents search your documents, databases, and knowledge bases in real-time to provide accurate, source-cited answers, dramatically reducing hallucinations and ensuring responses reflect your current, authoritative information.
At QAOcean, we build production-grade RAG systems that go beyond basic document Q&A. Our knowledge agents handle complex queries across multiple data sources, understand document structure and relationships, support conversational follow-ups, and cite their sources for verifiability. We optimize retrieval accuracy, response quality, and latency for real-world performance.
What We Deliver
Document Ingestion & Processing
Parse, chunk, and embed documents from PDFs, Word files, web pages, Confluence, Notion, and other sources with metadata preservation.
Vector Database Architecture
Design and implement optimized vector storage with hybrid search (semantic + keyword), filtering, and multi-tenancy support.
Advanced Retrieval Strategies
Implement query rewriting, hypothetical document embeddings, re-ranking, and multi-step retrieval for high-accuracy results.
Source Citation & Verification
Every response includes source citations with links to original documents, enabling users to verify accuracy and build trust.
Multi-Source Knowledge Fusion
Combine information from multiple document collections, databases, and APIs into coherent, comprehensive answers.
Our Process
Knowledge Audit
Inventory your data sources, assess content quality, define access controls, and plan the knowledge architecture.
Ingestion Pipeline
Build robust ingestion pipelines with document parsing, intelligent chunking, embedding generation, and metadata extraction.
RAG Agent Development
Implement the retrieval and generation pipeline with query optimization, context assembly, and response formatting.
Evaluation & Tuning
Measure retrieval accuracy and response quality with automated evaluation, tune parameters, and iterate to production standards.
Tools & Technologies
Why Choose QAOcean
Frequently Asked Questions
Related Services
Industries We Serve
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