Pilots that never land
Most enterprise AI pilots show no measurable impact on the numbers. The gap is integration, not intelligence.
Forward-deployed engineering is how the AI industry ships systems that survive contact with real work. We bring the same model to mid-sized companies: a senior engineer who works inside your team and your stack, builds with your real data, and hands over a system your people can run.
A capable model is no longer the hard part. The hard part is the last mile: your data, your systems, your people.
Most enterprise AI pilots show no measurable impact on the numbers. The gap is integration, not intelligence.
Slide decks and workshops end exactly where the real work begins: inside your ERP, your inbox and your edge cases.
Senior AI engineers are scarce, expensive, and searches run for months. Most mid-sized firms cannot staff this in-house.
We work in fixed-length tours: an engineer embedded in your team, aimed at one outcome with a number on it.
We map the workflow, quantify the pain and agree the outcome and its acceptance criteria before anyone writes code.
Your engineer works inside your team and your stack, part of the week, with your real data from day one.
Eval-first development: the test exists before the feature. We ship to production and measure against the agreed KPI.
Documentation, training and a clean handover are deliverables. The engagement is designed to end, not to renew itself.
Working software in your environment, integrated with your tools and passing an agreed evaluation suite.
Everything built during the tour belongs to you. No lock-in, no license meter.
Knowledge transfer is contracted, not promised. Your people operate the system when we leave.
Every embedded week surfaces adjacent opportunities. You leave with the next builds already scoped.
A senior engineer who works embedded in your team and ships production software inside your systems until an agreed outcome is reached. The model comes from Palantir and is now how OpenAI, Anthropic and AWS deploy AI with their biggest customers. We bring it to mid-sized companies.
A freelancer fills a task and an agency delivers a scoped project. An embedded engineer owns an outcome: they work inside your team, integrate with your real systems, and are accountable for the result working in production, with knowledge transfer built into the engagement.
Typically 8 to 16 weeks, at a fixed price tied to one clearly defined outcome. Longer roadmaps are broken into consecutive tours, each with its own KPI.
Where it helps, yes. Part of the week on-site with your team is common in the first weeks; the rest runs remotely. We deliver in English, Italian, German and French across Europe.
Your team runs the system. If you want ongoing monitoring, evaluation updates and an improvement backlog, a light care retainer covers it, and any larger follow-up becomes its own scoped tour.
Tell us the workflow that should already be automated. We will scope a tour with a fixed price and a number to hit.