Three ways towork with us.

This is how most clients find us. Hiring a senior engineer locally takes around eleven weeks between search, interviews and notice. This takes two.

They work in your systems, not beside them: your repo, your issue tracker, your stand-ups, your review queue. A written update goes out daily and we demo working software weekly. Every pull request is reviewed by a second senior engineer of ours before it reaches you, so you get two people's judgement at one person's rate.

If it isn't working at the end of the trial, you stop. No notice period, no exit fee, and you keep everything that was built.

For work too big for one person and too urgent to hire for: a migration, a rebuild, or a date you've already told people about.

The lead owns sequencing and is your one point of contact, so your product manager isn't routing between four people who each know a quarter of the problem.

Pods can grow mid-engagement or shrink to a single engineer without renegotiating. Most of ours start at three and settle wherever the work actually needs.

Some teams don't need more hands. They need someone who's seen this go wrong before and can say so.

A fractional lead sets review standards, settles architecture arguments, sits in your hiring loop, and writes the decisions down so they don't leave with the person who made them.

It's the cheapest thing we sell and often the highest leverage, because it stops work that should never have started.

Scope, schedule and cost agreed line by line before work starts. Working software every week, not a progress bar.

We get the boring bits right (data model, types, tests, deployment, errors) so the product can actually be good. Handover docs are written into the scope, not sold as an extra once you're already in.

If the scope moves week to week, say so early and we'll propose a pod instead. Fixed price only works when the thing being priced holds still.

Most AI projects fail in the same place: the demo looks great, then nobody can say whether it's actually right. We work the other way round.

The evaluation set is written at the same time as the feature: real questions from your domain, with answers approved by people who would know. Every change after that is measured against it, so accuracy is a number you can put in front of a board.

Every model call has a cost limit, a latency limit and a fallback. If a database query would do the job, we'll tell you. That conversation is free and usually saves a lot.

Pipelines, warehousing, deployment, monitoring, and the connected-device work that feeds them. The least glamorous thing we sell, and usually the actual problem.

You finish with runbooks your own team can follow, not a dependency on us. If we keep operating something, we say so up front and price it separately.

We'll also tell you when the infrastructure is fine and the problem is somewhere else. That has happened more than once.

Nobody quotes a repair before looking. We spend five days writing an assessment: what exists, what is dangerous, what it would cost to make safe. Fixed fee, agreed in advance. That document is yours whether or not you continue with us.

Then we stabilise before we improve: tests around whatever breaks most often, a deployment process you can trust, and a written map of the system so the next person isn't starting blind.

We usually argue against a full rewrite, and we'll show you the numbers. Rewrites are how companies spend two years standing still.

We map how your team actually sells before touching the org. That usually means shadowing reps rather than interviewing managers, because what people say they do and what they actually do are not the same thing.

The result is normally taking more out than we add. Eight years of customisation is the usual thing standing between a sales team and their CRM.

Because we also build the products around it, integration is done by the same people. No handoff between a platform vendor and an engineering vendor, and no argument about whose fault it is when the sync fails.

Marketing teams are usually not short of tools. They are short of numbers they can defend.

We rebuild tracking around real product events rather than page views, reconcile it against your database, and restate historical reporting where it has been wrong. The method is written down. We don't quietly change the figures and hope nobody checks.

Then automation that fires on what customers actually did, and landing systems your marketing team can use without booking a developer for every campaign.