A team of 4 that ships what takes 8 to build

AI handles code generation, tests, and documentation. Your engineers stay focused on architecture, business logic, and technical decisions. We accelerate delivery.

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Does this sound familiar?

Growing Backlog

Your team has 4–8 developers, but the backlog keeps growing.
Hiring Bottleneck

You opened a senior role three months ago and still haven't filled it.
Engineering Waste

Developers spend more time on boilerplate than business logic.
Previous Experience

You tried outsourcing before, and the code didn't work.
Team Growth

New developers onboard in days instead of weeks.
Business Pressure

Investors expect faster delivery without doubling engineering costs.
Leadership Overload

Your CTO spends more time managing execution than driving technical strategy.

Accelerate Your Software Delivery

We help engineering teams reduce development time by up to 40% through strategic AI implementation, automating repetitive tasks, accelerating decision-making, and enabling faster delivery without compromising product quality or technical standards.

See how it works

Why a dedicated AI team is productive

AI writes the routine, seniors review everything
AI generates boilerplate code, unit tests, type definitions, and migration scripts in minutes. Senior engineers spend their time on the things that actually require their judgment: architecture decisions, edge cases, performance-critical paths.
We execute what you plan
Every PR goes through your review process. Every architectural decision gets cleared with you first. We don't redesign your system, instead, we build what you specify, faster than a traditional team would.
Documentation that actually exists
Ever opened a codebase and realised the only person who understands it left six months ago? Documentation is generated while development is happening. The next developer doesn't spend weeks figuring things out.

Expected results

~40%

a typical sprint is routine work that AI handles directly: tests, docs, boilerplate, data mapping

2 wks

from the signed agreement to the first merged PR in your repository

4–6×

faster onboarding for future team members, because the codebase is documented from the start

1 sprint

is all you need to commit before deciding, and real output comes in 2 weeks

From the call to the first sprint

Here's exactly what happens.

Discovery call

We ask about your stack, your current team size, where the bottleneck actually is, and what "done" looks like for the next 8 weeks. You leave with either a concrete engagement plan or a business case document, and with a cost comparison and timeline ready for your CFO or board.
Technical assessment

We select engineers based on your specific stack. They spend the first few days reading your repo, understanding your patterns, and asking the right questions before writing a single line.
Pilot sprint

We start with a single well-defined module or feature. At the end of the sprint, you have working, tested, documented code reviewed by your team, merged by your process. This is the proof of concept before anything scales.
Evaluate results

If sprint one delivers what it should, we agree on scope and cadence going forward. If something's off, we address it, or you walk away. The first sprint is designed to make that decision easy.

Case Study

30 hours every week of manual work were eliminated

Client

Könner & Söhnen. Multi-regional ecommerce business operating across multiple European markets. Product information, pricing and inventory updates were handled manually across several stores.
The problem

Every price change, stock update, and product spec had to be applied manually. With 6 markets and thousands of SKUs, the operations team was doing data entry work for 30+ hours a week.
What we built

A fully automated sync pipeline using n8n, connecting their ERP to all 6 Shopify stores. Prices, inventory, product specs, and translations now update automatically every 2 hours across every market. No manual steps anywhere in the chain.

2 hrs
automatic sync across all 6 markets: down from manual updates that took days to propagate
8 wks
from kickoff to fully live across all stores and markets
30 hrs
of manual data entry eliminated every single week

See what we can automate for you