AI assistance

Move off a legacy engine at the speed of code

Migrating interfaces between engines is usually a re-platforming project measured in months. MessageFoundry treats it as a code review instead: an AI coding assistant in your editor reads your existing channel logic and drafts the equivalent Connections, Routers, and Handlers in Python — which you review, test, and promote like any other change. It's code-only by construction and governed by a central policy, so nothing leaves your control.

Why it's fast

Your logic becomes plain, reviewable Python

Legacy engines lock integration logic inside proprietary scripts and GUIs — JavaScript channels, Tcl, ObjectScript, XML buried in a database. Porting it by hand means relearning each system and rebuilding interface by interface.

MessageFoundry's configuration is code, so the assistant can do the mechanical translation for you: paste a legacy channel or open its export, and it drafts the matching inbound / outbound Connections, a @router, and the @handler transforms in Python. You stay in control — every line lands as a diff you read, adjust, and approve.

What it drafts for you

  • Connections — MLLP and file endpoints mapped from your existing source/destination config.
  • Routing — a @router that mirrors your channel's filter and routing rules.
  • Transforms@handler functions that reproduce field mappings and reshaping as pure Python.
  • Tests — starting points for harness scenarios so you can prove parity before cutover.
Legacy → modern

The same interface, two eras of tooling

The legacy way

  • Logic locked in a proprietary language (JavaScript, Tcl, ObjectScript) and a vendor GUI.
  • Configuration exported as XML or held in a database — hard to diff or review.
  • Migration is manual re-platforming, channel by channel, by scarce specialists.
  • Testing and promotion live in separate, proprietary tooling.

The MessageFoundry way

  • Logic is plain Python in your git repository — read it, diff it, own it.
  • The AI assistant drafts that Python from your legacy logic, in your editor.
  • Review as a pull request; dry-run in the included test harness on synthetic data.
  • Stage → Promote to a running engine — no separate platform to learn.
The migration loop

From legacy channel to running route

Point the assistant at your legacy logic

Open or paste an existing channel — a Mirth transformer, a Cloverleaf Tcl proc, a Rhapsody filter. That's source code, so it stays within the assistant's code-only scope.

It drafts the MessageFoundry equivalent

You get Python Connections, a Router, and Handlers that mirror the original's routing, filtering, and field mapping — wired by name, ready to read.

Review it like any code change

The draft lands as a diff in your editor and your pull request. Adjust, comment, and approve — the migration is now a normal review, not a black box.

Prove parity in the test harness

Dry-run synthetic, PHI-free messages through the new route and compare before/after. The headless scenario runner keeps the check green in CI.

Stage → Promote, then repeat in parallel

Promote the verified route to a running engine. Because each interface is independent code, a team can migrate many channels at once instead of serially.

Governed & PHI-safe

Code only — never message bodies

The assistant carries PHI implications, so it's controlled centrally, not per developer. Whoever operates the install sets a single policy — from fully off to PHI-safe — and every workstation honors it.

Migrating doesn't expose patients. Channel logic is code, and code is all the assistant sends. Your historical messages and live PHI never go to a model during a migration — the work happens entirely on the integration logic.

Bring your interfaces into the modern era

Open, Python, and AI-assisted — migrate off a legacy engine without a re-platforming project.