Real Knowledge Retrieval, Not Just Q&A
A production-grade RAG pipeline with hybrid search, knowledge graphs, source attribution, and intelligent chunking. Your agents give accurate, cited answers from your actual documents.
From Document to Accurate Answer
A six-stage pipeline that transforms raw documents into cited, accurate answers. Every stage is configurable, observable, and production-hardened.
Ingest
Upload documents in any format
Chunk
Smart semantic splitting
Embed
Generate vector embeddings
Retrieve
Hybrid semantic + keyword
Re-rank
Cross-encoder scoring
Generate
LLM answer with citations
Hybrid Search: Best of Both Worlds
Pure vector search misses exact keyword matches. Pure keyword search misses semantic meaning. OrchStack combines both — semantic embeddings and BM25 keyword scoring — fused with Reciprocal Rank Fusion for retrieval that actually works.
Semantic Vector Search
Understands meaning and intent. Finds related content even when exact words differ.
BM25 Keyword Search
Precise term matching for product names, codes, and technical identifiers that embeddings miss.
Reciprocal Rank Fusion
Intelligently merges both result sets into a single ranked list that outperforms either method alone.
Every Answer Cites Its Source
No more hallucination black boxes. OrchStack traces every generated answer back to the exact source passage, document, and page.
What is the refund policy for damaged items?
Damaged items can be returned within 30 days of delivery for a full refund[1]. You need to provide photos of the damage and the original order number[2]. Refunds are processed within 5-7 business days[1].
Upload, Version, Organize
Knowledge bases are not set-and-forget. OrchStack gives you a complete management layer — upload new documents, track versions, organize by collection, and monitor freshness. All from the Studio UI or API.
Knowledge Bases
Complete Knowledge Infrastructure
Every component you need to build knowledge-powered agents that give accurate, cited answers.
Hybrid Search
Combines semantic vector search with BM25 keyword matching for best-of-both-worlds retrieval. No more missing obvious keyword matches or failing on nuanced queries.
Knowledge Graphs
Automatically extract entities and relationships from your documents to build a navigable knowledge graph. Query by relationship traversal, not just similarity.
Source Attribution
Every answer cites its source — document name, page number, paragraph, and confidence score. Your users always know where the information came from.
Auto-chunking
Intelligent document chunking that respects semantic boundaries — headings, paragraphs, code blocks, tables. Configurable overlap, size, and strategy per document type.
Multi-format Upload
Ingest PDFs, DOCX, Markdown, HTML, CSV, JSON, plain text, and even images with OCR. Drag-and-drop or programmatic upload via API. No format conversion headaches.
Re-ranking
After initial retrieval, a cross-encoder re-ranker scores and reorders results for maximum relevance. Dramatically improves answer quality on complex queries.
Knowledge Engine FAQ
Power Your Agents with Real Knowledge
Build knowledge bases that make your agents genuinely useful.
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