Video library
Short explainers on semantic layers, text-to-SQL accuracy, AI agent governance, RAG, knowledge graphs, and the company brain.
Ask three teams for Q3 net revenue and you get three different answers. A semantic layer gives every metric one governed definition, so every team and every AI agent gets the same answer.
A semantic layer defines your metrics; a semantic execution layer delivers them. Why runtime SQL generation breaks at AI scale and a semantic compiler fixes it.
Bad data costs the average enterprise 12.9 million dollars a year and 95 percent of AI pilots deliver zero impact. A company brain is a living, governed map of how your business works.
Cortex Analyst and Genie lock metrics inside each warehouse. Why business meaning needs a horizontal semantic layer that sits above every system, with no rip and replace.
A catalog describes data, but nothing in the query path depends on it, so governance stays advisory. Why AI needs a semantic layer whose definitions compile into every query.
AI agents write their own SQL at machine speed and no human reads it. Govern them at compile time with seven layers: identity, meaning, policy, query validation, execution, response guard, and audit.
MCP collapses M by N integrations into M plus N, but two agents on the same wire can still disagree about revenue. Put a semantic layer behind the wire so agents get governed answers.
Three independent benchmarks agree that text-to-SQL collapses on real warehouses: Spider 2.0, MIT BEAVER, and Snowflake own tests. It is a context problem, and explicit structure closes it.
A knowledge graph maps what is related; a semantic layer computes what is true. Graphs win reasoning, semantic layers win metrics, and the strongest architecture layers both.
RAG retrieves what looks right; a semantic layer compiles what is true. Ranking by relevance is not ranking by correctness. Why the mature architecture stacks them instead of choosing.
A real semantic layer is eight capabilities, not two. The build is easy; the maintenance never ends. The asymmetric math of build versus buy and a three-year TCO comparison.
95 percent of AI pilots deliver zero impact. The 5 percent that win have three deterministic foundations: a semantic contract, a governance perimeter, and a schema feedback loop.
