Use case
Stewardship without the manual stitching
AI-assisted descriptions, tags and cross-platform lineage, so stewards review the context agents rely on instead of authoring it by hand.
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
Context for modernisation
Lineage and meaning from mainframe code, so modernisation agents and engineers work from the same verified map — before, during and after migration.
Read moreContext for compliance
Evidence-backed lineage for BCBS 239, DORA, GDPR and the EU AI Act — for figures produced by people and by agents alike.
Read moreContext for engineering agents
Coding and data-engineering agents see what a column means, what depends on it and what a change will break — across legacy and modern systems.
Read more
Give your stewards their week back
A pilot on one representative repository shows how much of the backlog is automatable.