Use case
Stewardship without the manual stitching
AI-assisted descriptions, tags, and cross-platform lineage, so stewards spend their time reviewing rather than authoring.
The situation
Documentation, tagging, and lineage stitching consume steward time that should go to judgement: reviewing, approving, resolving. Metadata written by hand is stale the week after it is written.
What Semantic Scout does about it
Documentation that writes its first draft
AI-assisted descriptions, tags, and glossary links, with version history. Stewards review and approve instead of starting from an empty field.
No manual stitching
Cross-platform data flows are connected automatically, including the joins between systems that normally need somebody to remember them.
Impact analysis for code changes
See what a change touches before it ships, rather than discovering it in a broken dashboard on Monday.
Proof
Used at a Nordic telecom to enrich tens of thousands of assets with automated metadata.
“No manual efforts anymore and our users are happy with the automated rich metadata.”
Customer names are withheld by agreement. Roles and industries are accurate.
Other use cases
Mainframe understanding & migration
Lineage from mainframe assets, COBOL programs explained through chat, and migration impact analysis backed by evidence.
Read moreRegulatory compliance
Continuous, column-level lineage and PII classification that turn BCBS 239, DORA, GDPR, and EU AI Act evidence into a by-product of normal operation.
Read moreAI-ready governance
Machine-readable lineage and meaning that give agents — and the people reviewing them — governed context and one-click provenance.
Read more
Give your stewards their week back
A pilot on one representative repository shows how much of the backlog is automatable.