AI-MSL (AI-Managed Software Lifecycle) is CloudGeometry's managed delivery model for enterprise software. Instead of a traditional staff-augmentation or rewrite approach, AI-MSL plugs into the systems you already run and executes continuous work across four fronts: proactive maintenance, new feature development, application modernization, and managed production operations. Its pitch is a pay-per-change commercial model that aligns spend with delivered outcomes, plus a DevCredits/appraisal flow that estimates work before it starts.
On the maintenance side, AI-MSL continuously scans an indexed inventory of your systems for dependency drift, security risk, deprecated APIs and framework end-of-life, producing a prioritized action list that your team approves. New features are handled differently: product managers and customer success teams describe intended behaviour in plain language, and the platform translates that intent into requirements specs, work items, code, tests and documentation. Every stage passes through expert review, and approved changes are tracked with full lifecycle traceability.
The modernization story leans on AppGraph, a continuously maintained semantic model of architecture, APIs, workflows and dependencies. AppGraph gives both humans and AI agents a dependency map for impact analysis, which reduces the risk of large change and supports governed AI-agent deployment through LangBuilder, CloudGeometry's open-source agentic workflow platform. Production operations run on a Kubernetes base spanning AWS, Azure and Google Cloud, and closes the loop by feeding reliability, cost and performance findings back into the requirements pipeline.
Because the offering is delivered as a managed service rather than a self-serve SaaS product, pricing is scoped per engagement and per change — there is no public list price, and buying happens through a system assessment and sales conversation.
