DaDaBIK + Jev AI: turn free text into actionable data

Posted by Eugenio on 1 Oct 2026

Dear users,
You may have heard about Jev, TypeSafe AI's new model, released just two weeks ago and designed for fast, structured decisions inside software.

I built a small IT ticketing application in DaDaBIK to see how naturally Jev could fit into a real application.

A user simply writes something like:

“The office Wi-Fi is down for everyone.”

DaDaBIK sends the ticket to Jev, which automatically determines its category, priority and confidence. Those results are then stored as normal database fields and can immediately be used for filters, dashboards, assignments, notifications and workflows.



You can think of these as a new kind of AI-calculated field: instead of calculating a value with a formula, the field is derived from the meaning and context of the data entered by the user.

And ticket classification is just one example. The same pattern can be used for CRM lead qualification, customer feedback analysis, document classification, expense approval workflows and many other DaDaBIK applications.

I show the complete integration, including the DaDaBIK after-insert hook and the Jev API call, in a new YouTube video: Watch the video.

What I particularly like about this approach is that AI becomes part of the normal application workflow rather than something separate from it. Jev produces structured information, DaDaBIK stores it in ordinary fields, and from that point on the rest of the application works exactly as usual.

I think AI-calculated fields could become a very interesting pattern for DaDaBIK applications and I'm already thinking about how this kind of integration could be made even more native in the future. Let me know what you think!

Best,

--
Eugenio Tacchini
Founder, DaDaBIK