Bring us the hard problem in your company. We compare the approaches, build the one that holds under failure, and leave you the code and the reasons. Integrations, document pipelines, models with an evaluation, orchestration you can operate. Fixed price. You keep the code.
We sit with the person who runs the work. We write the problem: what the team does, which systems it touches, and where it fails. You leave with that written down, and a recommendation: build this, or do not.
You walk away with
We build the fix on your data, in the systems you already run. The code sits in a repository you can open while we work, so you can see how it is going. You watch the job run on your real records.
You walk away with
The work is already done. These last days record why this approach, what we set aside, what it costs to run next month, where the data sits, and what breaks off the sample.
You walk away with
Most of these tasks have more than one workable fix. We look at the real case, try the options that fit, and write down the one we keep, the ones we set aside, and what it costs to run.
Tell us the problem the team already has. We come back with dates and a fixed price. You get a write-up of how the work happens today, the fix on your data, and a plan to keep it running. When the work is finished, we leave.
Contact usWhat you get
You send a problem the team already has. We go to the problem, understand it, and apply the technology that fits. We compare the approaches, including the one we set aside, and the technical plan records the monthly cost, where the data sits, and what breaks off the sample. We do the work until the problem is solved. You keep the code and the plan to keep it running. Then we leave.
We're a technology lab. We pick the tool that keeps working: a check in code, an integration, or a model. A file the team already touches is often a check in code, with no token bill. When a model is the right tool, the technical plan states what it costs to run next month.
An AI model that fits the problem. Answers from the source, or a refusal. Documents you can check. The same record in both systems. A job you can see fail. An update that lands once. If the work already happens, we can take it.
Yes, when it comes from a problem the team already has. We compare options and pick the approach that fits. We are a lab, not a software house, so we do not build a CRM, an app, or a platform from scratch when there is no problem to solve. If that is the ask, we say so before any build.
A team that already has the problem, and a person who needs the architecture defended. Your engineers can argue it with us. A manager can still own the outcome. Company size is secondary.
Either. Company size does not matter. We need a problem the team already has. 'Add AI', with no problem to solve, is not the work we do.
The owner does not have to be an engineer. Your engineers can argue the architecture with us. The handoff is the repository and the technical plan. A manager can still follow the call.
Three phases. We write how the work happens today. We build the fix on your data. Then you get a plan to keep it running. The work is finished. You keep the code.
2 to 5 weeks on the calendar when the owner and the files are available in week one. The diagnostic is 3 to 5 days, the fix is 1 to 3 weeks, and the technical plan is written in the last days, once the work is done. Two weeks is the small case: one export, one document type, or one sync, with the files already in hand. Waiting for access is not lab time.
A write-up of how the work happens today, the fix running on your data, and a plan to keep it running. The work is finished. You keep the code.
The hours in What we need from you: the person who does the work, about 30 minutes to pick an approach, the data, and a handoff call. We do the lab work.
Depends on the systems, data quality, and how complex the exceptions are. We understand the problem, then send a fixed price, locked before code.
Payment is split into two parts: 50% upfront to start the project and 50% before final delivery. One price for the whole three-phase project.
We look for that in the diagnostic, before any build. If a simpler path solves it, we say so. That is how the experience saves you the cost of the wrong project.
A1 Lab is new, so there is no client list yet. The lab has a master's in Computer Science and 12+ years in software engineering, including work for US companies.
Yes. We sign an NDA when you need one. Before we build, the technical plan says where the data sits: your systems, a controlled environment on our side, or an API under an agreement that does not train on your data. When privacy requires it, the model runs on your infrastructure or ours, and nothing goes to an external API.
Let's talk about your case
Tell us the problem in a few lines. What the team does today, and where it breaks. We reply the same business day.
What happens next
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