AI and machine learning
LLM assistants, search across internal documents, forecasts built on your data
We put together a team for your task, or take the whole project. Fintech, healthcare, industry: from a first working version to systems handling thousands of operations per second.
years on the market
Fintech, healthcare, industry
projects
Shipped to production, not to a demo
to find an engineer
From your request to their first day
extend the contract
After their first project with us
Four things we do on every project, whatever the budget, the industry or the engagement model.
We break the task into pieces and agree on what goes into the first version
We pick the numbers we will measure the result by, before we start
We staff the project with engineers who have solved this kind of problem before
We call the job done when the system is running in your production
Six areas of work. Take one, DevOps for instance. Or hand over the whole product, from the first user interviews to post-launch support.
Fintech, healthcare, construction, crypto exchanges. For each project we show what changed in numbers. The rest is under NDA.
Four stages. At each one you know who is responsible, what you get at the end of it, and by when.
We sit down together and take the task apart: what comes first, where the risks are, which numbers will tell us it worked. You get a list of work items and dates.
We pick engineers who match your stack and your industry. We agree on response times, what the reports look like, and who makes the calls.
Short iterations, with testing and deployment at every step. Once a week we show what is finished and re-check priorities.
We write the documentation, train your team, and leave you the contact of an on-call engineer for when something breaks.
Four areas where we have engineers who have built this before and seen how it behaves under load.
In fintech and healthcare a data leak can cost the client their licence. So here is what we do by default, before the contract is even signed.
Write us a couple of paragraphs about the task. We will read it, come back with questions and suggest how to approach it