AI DevOps · United States
AI-powered software development and maintenance service with expert governance and system intelligence
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AI-MSL is a managed service that develops and maintains software using AI-powered lifecycle execution under expert supervision, delivering changes at 70% lower
AI-MSL is a managed software development and maintenance platform that combines AI automation with expert engineering governance. It operates through a structured AI-driven lifecycle where product owners describe changes, AI-assisted tools refine requirements into production-ready PRDs, and AI execution performs implementation under expert supervision at five review gates. The platform uses AppGraph—a semantic system intelligence layer—to capture complete context about code, documentation, architecture, and infrastructure. Organizations pay per software change delivered rather than retaining development teams, with continuous maintenance keeping systems secure and modern while new features are estimated, approved, and delivered with full traceability and enterprise governance built in.
Pricing model: Paid
DevCredits pricing model where costs vary by change complexity. Monthly Continuous Software Readiness maintenance package covers routine updates and small enhancements. New features purchased individually as DevCredits or in discounted bundles: 200 DCs (save 5%), 500 DCs (save 10%), 1,000 DCs (save
AI-MSL replaces the need to manage development altogether through an end-to-end AI-powered lifecycle with governance. It operates on system-wide context (AppGraph) and enforces a governed lifecycle with supervision, ensuring all changes remain coherent, validated, and production-ready. Unlike individual AI assistants, it manages the full software delivery process with expert oversight.
You retain full ownership of your code, repositories, and all generated assets. AI-MSL operates on your system similarly to a development vendor or internal team with full traceability, structured changes, and consistent lifecycle governance. There is no lock-in to proprietary formats or hidden dependencies.
AI-MSL follows the same or stricter security model as working with a trusted engineering team. Your code remains in your repositories, access is controlled and auditable, data is not used to train external models, and outputs are stored in your environment.
You need access to your system and the ability to describe your goals. AI-MSL builds system understanding from your existing assets and improves it over time. You don't need perfectly structured documentation—the system evolves its understanding as it works with your codebase.
The assessment stage delivers a structured understanding of your system (AppGraph), visibility into dependencies and risks, identification of modernization opportunities, system quality evaluation, and cost estimates for future maintenance and feature development, replacing uncertainty with a data-driven baseline.
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