A senior AI-native engineering pod, embedded in your team, owning delivery from roadmap to production.
One fixed monthly price per pod. In the first 14 days you get a written technical memo: what is actually blocking the work, what we would build, what it costs, and what could go wrong. If it does not hold up, you walk away and keep the memo.
Four situations, in plain language.
The roadmap is slipping and headcount is frozen.
You get a pod, not a req. It starts inside your repos and your standups in weeks, and the cost is one fixed monthly line item you can defend to finance.
AI features work in a demo and die before production.
We treat evaluation, data plumbing, and failure handling as the actual work. A demo is not a deliverable; a system your on-call can support is.
Your best engineers are absorbed by maintenance.
The pod takes an entire delivery stream end to end so your seniors go back to the parts of the product only they can build.
Nobody in-house has shipped AI to production before.
We have, repeatedly, and we leave the pattern behind — the evals, the prompts, the pipelines, the runbook — so your team can run it without us.
What a pod actually is.
We work inside your organization — your repos, your tickets, your standups, your stakeholders. Not over a statement of work thrown across a wall.
AI is in how we build (codegen, review, test generation, retrieval over your own docs) and in what we build. We have worked this way since 2021.
A small senior unit with a lead who is accountable for the outcome. You do not manage individuals or chase timesheets.
We are accountable for something being in production and working — not for hours logged against a backlog.
Fixed monthly price. No timesheets, no change-order theatre.
Prices sit at the upper end of Indian offshore (€20–35/h for senior engineers) and well below Central European nearshore (€45–70/h). You get EU-hours overlap, GDPR-resident delivery and senior-only staffing at roughly €27–29 effective per hour — billed as one fixed monthly figure, not timesheets. per hour.
One scoped delivery stream
- One clearly bounded feature or service, from spec to production.
- You keep architectural authority; we bring the AI-native build practice.
- Weekly demo against written exit criteria, not status decks.
- Cancel at the end of any month after the minimum term.
A full stream we own end to end
- We own a whole product area: roadmap, build, evaluation, release, on-call handoff.
- Day-14 technical memo before you commit past the first phase.
- Production exit criteria agreed in writing before build starts.
- Documentation and runbooks written for your team, not for us.
Pod plus an upgrade of your own teams
- We ship a real system and, in parallel, move your engineers to the same working model.
- Tooling, review standards, eval harnesses, and internal enablement sessions.
- Measured against a maturity baseline taken in the first two weeks.
- Designed so the pod becomes unnecessary — that is the success condition.
Pricing is per pod, per month, quoted after the scoping call and fixed for the term. Travel and third-party licences are billed at cost and only with prior written approval.
Systems our engineers have already put into production.
No logos and no client names — most of this work sits under NDA. What matters for your decision is the shape of the problem, so that is what we publish.
Predictive maintenance for connected equipment
Telemetry from globally deployed machines feeding failure forecasting, so service visits are scheduled before the equipment stops.
Lab equipment management and alerting (LIMS)
Real-time capture from analytical instruments, operator dashboards, and instant alerts to mobile so intervention happens during the run, not after it.
Automated point-cloud classification
LiDAR segmentation of ground, vegetation, buildings, poles and conductors — replacing weeks of manual vectorization per survey.
ML model for clinical trial budget forecasting
A model predicting budget adjustments from changes in live trial data, used by a sponsor running multi-phase drug trials.
Resilient online banking platform
Admin, web, and customer applications built as one system, with the compliance and availability constraints designed in from the start.
AI agent for structured job data extraction
An Amazon Bedrock agent that turns unstructured postings into structured, matchable records inside a recruitment platform.
3D CAD digital twins of grid infrastructure
Terrestrial LiDAR turned into accurate substation and overhead-line models for a distributor modernizing toward smart-grid operation.
Field reporting app with cloud middleware
Hundreds of sites reporting labor, machinery and materials daily from tablets, with middleware reconciling it into back-office systems.
From first call to code in staging.
Every step has a written exit criterion. If a step fails its criterion, we say so in writing rather than rolling into the next phase.
Worth a call — and when it is not.
- You are a CTO, VP or Head of Engineering or Product with a stream that has to ship this year.
- You have real users, real data, and real constraints — not a greenfield idea deck.
- You would rather buy an accountable outcome than manage five contractors.
- You want your own team to be better at this after we leave.
- You want bodies at the lowest hourly rate, managed entirely by you.
- You need a fixed-scope, fixed-date build with no discovery and no memo.
- There is no internal owner who can make decisions inside a week.
- The goal is a demo for a board meeting, not a system in production.