AI Services — Run & Scale
The system works. Almost nobody understands why anymore.
A PMS integration layer, a custom IoT device gateway, an in-house billing module — built years ago, still running, and now understood by one person who's about to leave. AI-assisted analysis can map, document, and safely refactor these systems faster than a manual audit, without the risk of a full rebuild from scratch.
How we run it
Assess, build, scale
Codebase Assessment
- AI-assisted code mapping — dependencies, dead code, and undocumented business logic surfaced automatically, then verified by our engineers.
- Risk assessment — which parts of the system are safe to touch and which need careful handling because they connect to live devices, payment processing, or patient records.
- Modernization roadmap — a prioritized plan, not a blanket “rewrite everything” recommendation.
Guided Modernization
- Automated documentation generation for the parts of the system that had none.
- Incremental refactoring — module by module, tested at each step, so the system stays live throughout.
- Test coverage added before refactoring touches business-critical logic, particularly around billing and device-integration code.
- Migration support where the roadmap calls for moving off an unsupported platform or database.
Ongoing Modernization Support
- Continued incremental modernization as priorities shift.
- Documentation kept current as the system evolves post-modernization.
- Knowledge transfer so institutional knowledge isn't concentrated in one person again.
Where this comes up
Where this comes up most
- A hotel group's custom PMS-to-channel-manager integration, built in-house a decade ago, now blocking a multi-property rollout.
- A hospital's legacy billing module that nobody wants to touch because the one engineer who understood it has moved on.
- An IoT device gateway written for hardware that's since been replaced twice, with the codebase never fully updated to match.
FAQ
Common questions
Is this safer than a full rewrite?
Usually, yes — incremental, AI-assisted modernization keeps the system live and testable at every step, rather than betting the operation on a big-bang replacement.
How do you avoid AI misunderstanding undocumented business logic?
AI-assisted mapping surfaces candidates for review — every finding is verified by an engineer against actual system behaviour before anything gets changed. This is assisted analysis, not automated rewriting.
What if the system touches live guest or patient data during modernization?
Those modules get flagged during Assess as requiring extra care — additional test coverage and staged rollout before any change goes live.