AI engineering, at scale.
We provide architecture and advisory services to engineering teams shipping production AI systems. The work draws on years of delivering applied AI inside Fortune 100 enterprise software companies: AI tooling rollouts across 2,000+ engineers, agentic system architecture, and applied AI portfolios used by tens of thousands of enterprise developers.
Three ways to engage.
AI architecture reviews
Senior architectural review of AI systems being built or already in production. We look at model selection, retrieval, evaluation, prompts, observability, and security posture, then write up where the system will break at 10x scale and what to fix first. Deliverable: a written assessment with prioritized recommendations.
Best fit for: teams that have shipped an AI feature and want senior eyes on the architecture before scaling.
AI-augmented engineering rollouts
Helping engineering organizations actually get value from AI dev tools (Claude Code, Copilot, Cursor, Cline). Most rollouts hit 5–10% productivity gains. Well-run ones hit 25–30%. The gap is strategy: which tool for which team, how to train, how to measure, and the cultural work that decides whether the licenses get used or sit on a shelf.
Best fit for: engineering organizations of 50+ people that have purchased AI dev tools but haven't seen the productivity gains promised in the marketing.
Applied AI advisory
Ongoing advisory for technical leadership making AI decisions: build-vs-buy, vendor selection, architecture tradeoffs, hiring for AI roles. Plus the smaller calls that pile up between them and decide whether the initiative actually ships. Typically 4–8 hours a month, with calls when something can't wait.
Best fit for: founders, CTOs, and VPs of Engineering who want experienced perspective without committing to a fractional CTO arrangement.
What you can expect.
Senior people on senior problems
Engagements are led by Centractive principals with extensive experience delivering applied AI at Fortune 100 enterprise software companies. We don't hand AI architecture decisions to people who learned about LLMs last year.
Honest scoping
We'd rather decline an engagement than overcommit. If we don't think we're the right fit for what you need, we'll tell you that directly and point you to who might be.
Defined deliverables
Every engagement has clear deliverables and a clear endpoint. Time-boxed reviews finish on schedule. Project-based work has milestones. Advisory engagements can be paused or stepped back as your needs change.
If you're shipping an AI product and want to take it from startup to enterprise scale, let's talk.
A short note on what you're building helps us route it. First calls happen over video and run about 30 minutes.