A capability-by-capability map across five data platforms — catalog, SQL/BI, ingestion, AI/ML, sharing, and admin — with an honest maturity read on who leads where.
Six blogs, one architecture. A layer-by-layer blueprint for production agentic AI — from intelligent routing and GraphRAG knowledge cores to governed orchestration and AgentOps.
GraphRAG gave agents the Map. The Context Infrastructure Mandate gives them the Pilot—persistent decision traces, the Guardian Agent, and the SAO Context Graph that makes every autonomous action auditable.
How Agentic Governance replaces binary 403 blocks with a Stealth Remediation Loop—finding a compliant path to Yes so agents never stall.
How to orchestrate secure, flexible agent workflows in Python using LangGraph and YAML—no code changes required for routing updates.
Architecture, orchestration, GraphRAG, MCP, and safety patterns for production agentic systems.
How autonomous agents replace manual ETL and reporting with real-time, intent-driven workflows.
Four core pillars for AI-ready data architecture: Knowledge Core, semantic mesh, HTAP, and governance fabric.
Eliminating hallucinations and enabling multi-hop reasoning using graph-backed retrieval.
Fine-tuned small models outperform frontier LLMs on tool-call reliability, schema adherence, and multi-step agent execution — not as a substitute, but as a better fit.
Platform-agnostic blueprint for taking agents from demo to reliable production services.
Build resilient digital workforces using the 6-layer architecture: from sensing to execution, with human control at the center.
Shadow AI, prompt injection, and data leaks are bigger threats than hallucination. AI TRiSM is the operational framework to govern AI before regulators force your hand.
How the Semantic Sidecar enables robust, compliant, and agile AI systems by decoupling the semantic layer from the core application.