Data30 - Session 9: Collate 2.0. AI Has a Context Problem. We Solved It.
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AI is a decision multiplier. Multiplying a broken decision is not an improvement.
Every AI initiative raises the number of decisions AND the stakes on each decision your business makes per quarter. More answers, more analysis, more action, faster.
Good news only if the inputs are right. If they aren't, you haven't bought productivity — you've bought a machine that allocates capital incorrectly ten times faster, and retires the analyst who hesitated before sending the number up the chain.
Decision volume is going up either way. Decision Quality is the variable you still control. Ask an AI agent for "active customers". Four columns could mean that, nobody wrote down which. So your AI agent picks one. No bigger model fixes that..
That's what Collate 2.0 is for. Built on OpenMetadata's open context layer — trusted by 4,000+ enterprises and frontier AI labs — it adds what agents need: Connect. Reason. Remember.
Agents document, quality-check and tier the whole estate, not one initiative at a time. Ontology on open W3C standards captures how your business relates, so agents walk a typed graph, not a guessed schema. That grounding is why Collate dramatically improves text-to-SQL from 10.8% to 76.5% on the Spider 2.0-Snow benchmark and cuts token costs by upto 80% per agent call. AI Analytics answers in plain English, checks access, and promotes the chart to a governed, lineage-aware dashboard. AI Studio builds your own agents, no code, on your LLM, against one governed grounding. And memory settles a correction once, then applies it to every human and agent action that follows.
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