From documents to decisions: making unstructured content programmable with Jev

Published by Olga Stefaniuk, the piece presents Jev, TypeSafe’s “System One” AI model, as a tool for converting unstructured content into predefined, type-safe probabilistic decisions rather than generating conversational text. Drawing on Daniel Kahneman’s distinction between fast intuitive thinking and slow deliberative analysis, it describes Jev’s Choice, Score, and Noul primitives, which let applications classify, score, or answer boolean questions with confidence levels. A Box integration demo illustrates how a PDF incident report can be converted to Markdown, assessed for incident type, severity, and escalation need, then routed by explicit application rules into Escalate, Review, or Monitor folders while metadata and optional human review tasks are created in Box. The approach positions Jev as a semantic decision layer for operational documents, with AI interpreting ambiguous language and conventional software retaining transparent control over policies, thresholds, permissions, and consequential decisions.

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