AI runs outside. Value shows up inside.

AI and machine learning models are never embedded inside the PowerBuilder codebase. They run as independent services — a Python-based model, a cloud AI/LLM API — called over REST/JSON through a secure integration gateway. PowerBuilder never needs a rewrite, a runtime change, or a DLL/COM bridge; it simply calls out and renders the structured JSON response back into its existing DataWindows and Windows.

Every engagement starts as a proof of concept, not a program. One real AI use case, connected to one real PowerBuilder screen, running against your own data. You see actual output — extracted fields, a risk score, a plain-English answer — inside the tool your team already uses, before deciding whether to expand further.

The gateway is also the natural place to enforce data governance. Because AI capability lives at the boundary rather than inside the legacy application, authentication, request/response mapping, redaction, and audit logging are handled in one place — sensitive fields never need to leave that boundary ungoverned.