Use case
Change code knowing what it touches
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.
The situation
Coding agents now write and change the pipelines that produce your numbers. They read the file in front of them well. What they cannot see is everything around it: what a column means to the business, which reports and downstream jobs depend on it, and whether the same logic also lives in a program three systems away. An agent that changes code without that context ships a breaking change with full confidence.
What Semantic Scout does about it
Context your agents can query
Coding and data-engineering agents reach the same lineage and meaning your people do, directly over MCP and A2A, with the evidence attached. Any agent that speaks MCP can use it.
Impact before the change
Column-level lineage across legacy and modern systems shows what a change touches — reports, downstream jobs, the regulatory figure at the end of the chain — before it ships, not after it breaks.
Meaning that matches the code
Descriptions derived from the code itself rather than from documentation nobody updated, so the agent works from what the system actually does.
Evidence a reviewer can check
Every fact an agent relies on cites the file and line behind it, so a reviewer can check the agent’s reasoning instead of taking it on trust.
Proof
In production use at Nordic enterprises in banking and telecom. Our own chat over transformations is an agent grounded in the same context, working on the hardest estate there is.
“Auto generated descriptions for the data assets are so rich, better than human-written ones.”
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 moreData stewardship
AI-assisted descriptions, tags and cross-platform lineage, so stewards review the context agents rely on instead of authoring it by hand.
Read more
Give your agents something to stand on
See what evidence-backed context looks like against your own repositories, rather than a vendor sandbox.