A small lab for production ML.
We are engineers who would rather talk about your process than our stack. We put models into the workflow that already spends the money, agree the metric before training, and keep serving, monitoring and rollback in the same delivery.
- Founded
- 2025
- Core team
- Senior ML lead and ML engineers, specialists per project
- Where
- Minsk, Belarus · remote, CET business hours
- Contracting
- The proposal names the contracting party; payments go through Georgia
SwankyForge is a small engineering team. The case studies on this site are reference designs: each one shows how the before and after would be measured, and none is presented as a client result. We price with a public calculator that uses the same rates we would quote you. We are the right call when something costs too much or takes too long, and the wrong one when you need a demo for a board meeting.
We start with your problem, not our stack.
Most ML projects die of a communication failure, not a modelling failure. These are the working habits we hold ourselves to, and you can hold us to them too.
The first call is a conversation, not a demo.
We want the process that already spends the money, who touches it, and what breaks when it gets the answer wrong. No slides until we understand that.
One named engineer, start to finish.
The person who scoped your project is the person who ships it and the person who answers when it pages. No account-manager relay, no handover to a junior after signature.
We will tell you not to buy ML.
If a rules engine, a fixed report or better data entry moves your number more cheaply, we write that down and say so. It costs us a project and saves you two quarters.
Transparency is the default setting.
A metric registered before training starts. A written update every week, whether the news is good or not. The repository in your org from day one — nothing lives on our laptops.
Every technical decision gets a plain-language version.
Your CFO should be able to challenge our architecture without a translator in the room. If we cannot explain a trade-off in a paragraph, we do not understand it well enough yet.
We stay after launch.
Serving, monitoring, drift alerts and a rollback path ship in the same delivery as the model. A system nobody can roll back is not finished.
What you can hold us to.
Not outcomes — those depend on your data. These are the working commitments in every contract.
- 01
A working demo every week
Not a status report. Something that runs, on your data, from the second week on.
- 02
The repository lives in your organisation from day one
You own the code, the weights, the runbooks and the history. Nothing is held back until the last invoice.
- 03
Milestone acceptance before invoicing
Each milestone has written acceptance criteria agreed up front. You sign off, then we bill.
- 04
Monitoring and rollback ship before handoff
A dashboard on the metric you named, drift alerts, and a rollback you can trigger without us.
Got a cost line to move?
Answer six questions and we will tell you what we would actually do — including when the answer is that you do not need us yet.