We help software companies embed AI — reducing time to market and improving productivity, margins and quality.
You leave knowing where your delivery system is leaking margin — whether we work together or not.
The question is not whether teams use AI. It is whether AI adoption moves margin, growth and delivered value — or just activity.
AI can accelerate code and quietly multiply review burden and risk. Guardrails decide which of those you get.
Predictable delivery and a clear cost-to-deliver matter more than raw speed. We measure both against a baseline.
A €7M software consultancy grew to €9M in 12 months while improving profit per delivered hour by 15% — through OKRs, delivery discipline and AI-enabled workflows.
A software development consultancy tripled its development team's productivity after a three-week AI adoption program focused on AI-powered multi-agent systems.
A SaaS company completed an eight-month product roadmap in just three weeks during our hands-on program adopting AI-powered multi-agent systems.
Every number above has a baseline, a timeframe and a client who approved it. That is the only kind of metric we publish.
Managers expect productivity gains. Developers worry about quality. Leadership wants ROI. But the core problems often remain:
The issue is not access to AI. The issue is whether your workflows, quality standards and metrics have changed enough to capture the value.
No serious transformation.
No safe AI adoption.
No proof of impact.
| Week | Focus | Outcome |
|---|---|---|
| Week 1 | Diagnose | Delivery profitability leak map and AI maturity baseline |
| Week 2 | Prioritise | AI use case portfolio and risk map |
| Week 3 | Guardrail | Quality, security, review and validation standards |
| Week 4 | Pilot | Measured workflow experiment and go/no-go recommendation |
Operational load: your team invests 2–3 hours per week. No workshops that stop delivery. We work inside your existing rituals.
You will know where the opportunity is, what risks need to be controlled, and whether a bigger programme makes sense — or not.
Not every profitability problem starts or ends with AI. Sometimes the constraint is unclear product strategy, fragmented priorities, weak delivery flow or an operating model that cannot respond fast enough.
Turn AI adoption into measurable improvements in margin, predictability and quality, with baselines and engineering guardrails.
Improve how teams plan, collaborate and deliver. Replace ceremony-led change with a measurable roadmap focused on flow, value and business outcomes.
Connect customer needs and business strategy to product decisions through discovery, validated learning and value-based prioritisation.
Help leadership align strategy, structure, people, processes and technology so the organisation can respond to opportunities faster.
Build practical Scrum, Product Ownership, Kanban and Agile Leadership capability through courses applied to real working situations.
A 45-minute working session with Nicolás (not a salesperson, not a junior) for CEOs, CTOs, COOs and Heads of Engineering.
What this is not: a tool demo, a generic sales call, or agile coaching disguised as strategy.
The work uses the client’s real delivery system: backlog, pull requests, test strategy, coding standards, review process and Definition of Done.
Your code and data stay yours. NDA by default. No code leaves your environment. AI usage during the engagement follows your data policy, not ours.
The goal is not to make developers use more AI. The goal is to use AI where it improves quality, speed, learning and control.
One 45-minute working session. A written 30-day roadmap. Yours to keep either way.