Systems
The machinery behind the work. Built in-house, run in-house, auditable end to end.
All development at Kurolabs runs on in-house AI infrastructure. We self-host fine-tuned open-weight models and drive them through a customized harness — purpose-built tool loops, context management, and verification gates designed for systems programming. No third-party SaaS in the loop, no proprietary black boxes. Every model, every weight, every token is ours to inspect, audit, and improve.
Four parts, one machine.
Fine-Tuned Open Weight
Open-weight models fine-tuned on the corpora that matter: systems code, performance-critical patterns, and the failure modes we have actually hit. We distill per project; we do not rent intelligence.
Custom-Built
A customized agent harness around the models: typed tools, bounded context, deterministic replay, and verification gates that treat model output as untrusted input.
Self-Hosted
Our own GPU cluster, sized for the work. No per-token meter, no queue behind someone else's API, no dependency on a third party's uptime.
Closed Loop
Client code, prompts, and traces never leave the cluster. Confidentiality is a property of the architecture, not a clause in a contract.
Owning the stack is not a perk. It is the precondition for the work above.
The inner loop is measured in seconds, not API round-trips. Ideas become benchmarks before the coffee cools.
When the model misbehaves, we can read the weights, the data, and the harness. Nothing is a mystery we pay for.
Leverage at marginal cost, not at list price. Scale is a scheduling decision, not a billing dispute.
For NDA work, the audit trail is physical: machines we can point to. Show the client where every token went.
Bring Us a Problem That Needs This Machinery.
The stack is standing by. Read how we work →
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