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Services / Legacy System Integration

Legacy System Integration

Your legacy system holds the data. We build the bridge to AI — with you keeping control of both ends.

Who it's for

  • Organizations whose core system 'works fine' but can't talk to modern AI tools
  • Teams exporting spreadsheets by hand to feed reports and chatbots
  • IT leads who need AI capability without a multi-year platform migration

Typical problems we hear

  • Valuable operational data locked in a system with no API anyone has touched in years
  • Manual export–clean–upload routines that break whenever one person is on vacation
  • Legitimate fear that connecting AI to production data means losing control of it

What we do

  1. Assess the legacy system honestly: interfaces, data quality, and what integration patterns it can support
  2. Design the data flow so AI services receive the minimum data they need — and nothing else
  3. Build the connector incrementally: read-only first, human-approved writes until trust is earned
  4. Instrument and document: logs, failure handling, and a rollback path are part of the deliverable, not extras

Deliverables

  • A working, documented connector between your legacy system and the AI service
  • A data-flow diagram showing exactly what data moves, where, and why
  • Operational runbook: monitoring, failure handling, rollback
  • A phased plan for extending the integration safely

Questions, answered

Our system is old and undocumented. Can you still help?

Usually, yes — that's the common case, not the exception. The assessment exists precisely to find out what the system can support before anyone quotes a build.

Will AI services see all our data?

No. We design minimum-necessary data flows: the AI gets the specific fields the task needs, and the data-flow diagram is a deliverable you approve before anything is connected.

Do we have to replace our system eventually?

Not because of this. Integration buys the legacy system new capability; whether to replace it stays a separate, un-rushed decision.

What if something breaks in production?

Connectors ship with logging, failure handling, and a documented rollback. We start read-only and add write access in stages for exactly this reason.

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