Services
Most of what is sold as "AI strategy" is a slide deck and a vendor recommendation. What actually moves the needle is closer to the ground: how engineering ships, how the architecture absorbs AI decisions, how the portfolio surfaces itself to agents, and who you hire next. We help with each, together or individually.
AI-SDLC adoption and legacy modernization
Decomposing monoliths. Refactoring legacy data models. Documenting undocumented systems. Roadmapping the journey from "we bought some Copilot seats" to AI as a structural part of how engineering ships. Workshops, hands-on R&D sprints, and impact analysis, done by people who have run this exact program inside a regulated enterprise.
Explore AI for Software Engineering →AI-first architecture and accountable controls
How does your firm react when AI moves into production decisions? We help design IT architectures that support good governance and resilience for AI deployments, drawing on the MAS AIRM framework and parallel regimes. The focus is the financial-services case: building systems where AI decisions are defensible, explainable, and auditable end-to-end.
Explore AI Governance →Make the portfolio legible to agents and to humans
Instrument the application portfolio so that AI agents, and the humans relying on them, can actually discover, reason about, and impact-analyze your systems in real time. The precondition for any modernization, post-merger integration, or platform consolidation that does not stall once the first dependency surprise lands. The methodology draws on our published thinking on why modernizations fail.
Explore Portfolio Intelligence →Rebuild your engineering hiring
The interview questions that worked in 2014 are actively misleading in 2026. We help reframe engineering hiring around what now matters: the last agent the candidate wrote, the workflows they have automated, their fluency with prompting, spec-driven development, and agentic-centric development cycles. Plus support sourcing the lean leadership and engineering talent your AI initiatives actually need.
Explore Talent for the AI Era →Most engagements blend two or three. A short discovery call is usually enough to map your situation against the right starting point.
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