Who We Help
We work with engineering leaders at organizations where AI-enabled software delivery is a strategic priority, not just a technology experiment.
Our Clients
Engineering-led organizations ready for structured transformation
SaaS Companies (100–1000 Employees)
Product-led organizations where engineering velocity directly drives business outcomes. You've adopted AI coding tools but haven't seen the step-change in delivery speed you expected. Your engineering teams need a structured approach to move from individual tool adoption to systematic SDLC transformation.
Common Challenges
- AI tool sprawl without measurable velocity improvement
- Inconsistent adoption across teams and projects
- Need to maintain quality while accelerating delivery
- Competitive pressure to deliver AI-native products faster
Regulated Industries
Financial services, healthcare, government, and other regulated organizations that need AI governance alongside innovation. You recognize the potential of AI in software delivery but face genuine compliance, risk, and audit concerns that generic best practices don't address.
Common Challenges
- Regulatory uncertainty around AI-generated code
- IP and licensing concerns with AI tools
- Audit trail requirements for AI-assisted development
- Balancing innovation speed with compliance obligations
Enterprise Engineering Teams
Large engineering organizations (100+ developers) ready to move beyond scattered pilot projects to enterprise-wide AI-enabled delivery. You need transformation at scale — new operating models, new team structures, and new ways of measuring success.
Common Challenges
- Pilot projects that don't scale to the full organization
- Legacy processes that resist AI integration
- Change management across large, distributed teams
- Executive alignment on AI strategy and investment
Signs You're Ready
Common triggers that signal it's time for a structured AI transformation approach
- !Your AI coding tool licenses are growing but velocity metrics are flat
- !Engineering leadership is asking 'what's our AI strategy?' and the answer is unclear
- !Compliance or legal has raised concerns about AI tool usage with no governance framework in place
- !Competitors are publicly shipping AI-native products and your board is asking questions
- !You've done a pilot — it worked — but you can't figure out how to scale it
- !Your best engineers are frustrated by the gap between AI tool potential and organizational adoption
Sound Familiar?
Let's discuss how a structured approach to AI-enabled delivery can address your specific challenges.