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The trust layer between your scattered knowledge and your agents. Most enterprise AI fails at the data layer — dumb chunking destroys context, and stale retrieval acts on yesterday's truth. Knowledge Hub fixes both ends: it shapes raw data into agent-ready, confidence-scored structure, then serves it with freshness, verify-before-act and conflict arbitration. Not another search-everything platform.
Knowledge Hub is a work in progress, not a generally available product. The readiness half (structuring) is live today via Data Extractor; the currency half — currency-scored retrieval, verify-before-act and conflict arbitration — is still being built. This page describes where the product is headed, with each capability labelled by its current status.
Readiness is the write path — what happens before a query exists. Currency is the read path — what happens the moment an agent asks. One prepares, the other serves; together they're the difference between data an agent can reach and data it can trust.
Dumb RAG chops documents into random character-limit chunks, destroying hierarchy, tables, and relationships. Knowledge Hub parses logically instead — messy tickets, docs and PDFs become typed, source-anchored objects with a confidence score on every field. This half ships today as Data Extractor.
Retrieval tells you what exists; currency tells you what is true right now. Every answer carries a freshness signal and verified-at timestamp, agentic calls confirm against the source system before they act, and when two sources disagree you get the authoritative answer and the reason — not both. The serve path is in build.
Raw documents become typed, source-anchored objects with per-field confidence — not contextless strings. The exact shape an agent can filter and act on. Live today in Data Extractor.
Every piece of data is enriched with the context an agent needs to retrieve safely: permissions, timestamps, source links, and intent labels. Agents filter to exactly what the caller is allowed to see.
Every answer carries freshness + confidence + verified-at, so an agent can decide whether to trust it — or go re-verify before it acts. In progress.
A dedicated path confirms against the source system of record before an agentic action runs, so an agent never acts on a stale cached answer. In progress.
When two sources disagree, Knowledge Hub returns the authoritative answer and the reason it won — newer, source-of-record, or validated — instead of handing the agent both and hoping. In progress.
ServiceNow ITSM semantics first — SLA, configuration items, resolution validity — not a hundred shallow generic connectors. The connectors that understand the domain, before the ones that just read it.
We build the trust layer the way you'd actually trust it — readiness first. The structuring half is live in production today as Data Extractor: send text, an image or a PDF and get back typed, source-anchored objects with a confidence score on every field. The currency half — currency-scored retrieval, verify-before-act and conflict arbitration — is in progress. We'd rather ship the part that's real and say so than badge the whole thing “available” before the retrieval path exists.
The readiness half, shipping today — schema-driven JSON with per-field confidence and source anchors.
Calls the Hub when correctness matters — current, verified context behind every one-line pinpoint and intent signal.
Decides on data the Hub has made trustworthy — verdicts grounded in current, source-of-record knowledge.