AI-MSL packages are delivered as flat monthly services. Pricing is determined after the System Intelligence Assessment — based on your system's real architecture, not assumptions.
Usage of multiple AI models — Claude Code, Codex, and Gemini — included in every package.
Experienced engineering and AI professionals supervise every lifecycle stage.
A dedicated AI-MSL Service Manager who learns your system and works with your leadership.
Lifecycle governance and quality controls at every stage of development.
Continuous system context capture and analysis through AppGraph.
Personalized service designed for your organization's specific needs.
Choose how much of your software lifecycle
to move into AI-powered development.
Product definition and requirements intelligence grounded in real system context.
Finalized PRD ready for development teams or structured brief for AI-powered development.
AI-powered software development lifecycle. Requirements become production-ready code.
Everything in PM, plus:Features delivered next day — clean code, tests, docs, and a Git branch ready to review.
The entire software lifecycle managed by AI-MSL — from requirements to production operations.
Everything in Build, plus:Production updates delivered instantly with AI-powered deployment, monitoring, and cost optimization.
Deep integration with internal engineering processes and governance.
Everything in Operate, plus:AI-MSL operates alongside your internal team with full governance alignment.
Every tier builds on the last. Start where you are — expand as you scale.
Based on a typical active B2B SaaS product: customer portal, admin portal, backend APIs, data layer, integrations, infrastructure, and monitoring.
50/50 split between US-based and offshore personnel
Even without major features, engineers spend most time on bug fixes, dependency updates, infrastructure maintenance, and production issues.
AI-MSL costs reduce over time as the system learns and AI technology advances.
AI-MSL replaces a developer-dependent model with a managed AI-powered software lifecycle.
Companies no longer need to maintain a permanent engineering team just to keep their software evolving.
Pricing is determined after the System Intelligence Assessment — which builds AppGraph and analyzes your system architecture, dependencies, complexity, and AI-readiness.
Understand whether your system is a good fit for AI-MSL and what the expected cost will be. Build AppGraph, analyze architecture, determine AI-MSL service pricing.
Everything in Readiness, plus deeper architecture analysis, technical debt identification, modernization opportunities, and improvement roadmap.
Full long-term cost and sustainability analysis. Includes maintenance projections, operational risk analysis, team dependency evaluation. Ideal for acquisitions, investment analysis, or vendor transitions.
The assessment builds AppGraph — a semantic model of your software system — and produces a structured analysis of architecture, dependencies, quality, and operational complexity.
You receive a clear, data-driven understanding of your system and what AI-MSL service packages will cost.
Yes. Every system is different. The assessment ensures AI-MSL operates based on your real architecture, not assumptions.
Typically days to a few weeks depending on system size and complexity.
No. AppGraph captures information from code repositories, documentation, infrastructure configs, and other sources automatically.
Yes. Organizations often start with PM or Build and expand to Operate as they see results. The transition is seamless because AppGraph already understands your system.
AI-MSL operates across systems of all sizes — from focused SaaS products to large enterprise platforms. The System Intelligence Assessment determines the right scope and pricing.
AI-MSL packages are delivered as monthly services. We work to earn continued engagement through results, not lock-in.
The System Intelligence Assessment gives you a clear, data-driven understanding of your system and what AI-MSL service packages will cost.
AI-MSL is designed for organizations with existing production software. If you're building from scratch, this probably isn't the right fit.
