What changes for your team
- A question about your own data answered directly, instead of searching several systems by hand
- The record the answer came from shown alongside it, so it can be checked
- Nothing acted on automatically. Every answer is for your team to verify before using it
- No new system to search in: she only reads from what she's been given access to
What asking Vera a question looks like
You point Vera at the systems and records you want her to draw from. You ask a question about your own data the way you'd ask a colleague who knows where everything is filed.
Vera finds the answer and shows the record it came from, so your team can check the source before using it. She doesn't act on what she finds; she only answers and points to where she found it.
She answers only from what she's been given access to. Nothing beyond those systems, and nothing guessed.
This kind of work hasn't been deployed at a client yet, so there is no measured result to show. What's here is what she's configured to do, stated plainly rather than estimated.
Work experience
Not a career history. Just what has actually been demonstrated so far. For Vera, that's nothing yet: this kind of work hasn't run at a client.
Processing happens in Europe, under GDPR and the EU AI Act. Your data is never used to train AI models.
What she needs from you
This is new territory for her: she has no placement yet to draw experience from.
- Read access to the systems and records you want her to draw answers from, and nothing more
- Agreement on which systems are in scope, since she only answers from what she's been given access to
Expected, not measured yet. A real number goes here once she has run at a client.

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