Knowledge & Retrieval
RAG, knowledge graphs, semantic search, and information synthesis.
Agentic RAG
Agentic RAG puts the AI agent in control of retrieval decisions, dynamically choosing when, what, and how to retrieve information rather than blindly fetching documents for every query.
Document Understanding
Document understanding enables agents to extract structured, actionable information from complex document formats – PDFs, tables, images, spreadsheets, and scanned documents – through multi-modal parsing, layout analysis, and structured data extraction.
Dynamic Retrieval Decisions
Dynamic retrieval decisions determine when an agent should fetch external information versus relying on its own parametric knowledge, using confidence-based triggers and retrieval budgets to optimize for both accuracy and efficiency.
Hybrid Search Strategies
Hybrid search combines semantic search (embeddings), keyword search (BM25), and structured queries (SQL/graph) to overcome the individual weaknesses of each approach, using fusion techniques to deliver more robust retrieval results.
Knowledge Base Maintenance
Knowledge base maintenance is the ongoing operational work of keeping agent knowledge stores accurate, current, and performant through updating stale information, deduplication, versioning, incremental indexing, and contradiction resolution.
Knowledge Graph Navigation
Knowledge graph navigation enables agents to traverse structured entity-relationship networks for multi-hop reasoning, answering questions that require connecting facts across multiple nodes in ways unstructured search cannot reliably achieve.
Query Reformulation
Query reformulation improves retrieval quality by iteratively transforming user queries into more effective search queries through expansion, decomposition, and hypothetical document generation techniques.
Source Verification
Source verification ensures agent reliability by cross-referencing retrieved information across multiple sources, detecting contradictions, scoring confidence, and providing citations to prevent the propagation of incorrect or outdated facts.