Most AI programmes stall before they start —
not for lack of ideas, but for lack of a defensible first one.

Cob takes one business objective, in your own words, and returns a ranked set of AI use cases with the reasoning attached: why this one first, what it depends on, and what it would take to run. Not a workshop output — a starting point you can defend to the people funding it.

Start with your objective What Cob produces ↓

What it does

Three things Cob settles before you commit

Each one is generated from your objective and, where you connect them, your own Confluence and Jira content — so the output argues from your programme, not from a generic industry template.

Which use cases are actually available

Cob reads the objective and produces the candidate AI use cases that genuinely fit it — named in your own vocabulary, not translated into stock categories.

Which one to start with, and why

Every candidate is placed against business value and delivery feasibility, and one is recommended as the starting point with the reasoning written out — the part that survives the meeting where someone asks "why this one?"

What it will need to run

The recommendation carries its dependencies forward: the data it needs, where that data usually lives, and what is missing today — which is exactly what Aria picks up next.

Approving a use case in Cob is what starts the rest of the journey.

Why Svarg builds this ourselves

The first decision sets everything after it.

Aria, Arth, Eame and Yusu all inherit whatever Cob decides. Choose the wrong first use case and every stage after it is efficient work in the wrong direction. That judgement is the part clients are really buying, so it isn't something we hand to a partner.