Approach

Hourly, and scoped in the open

Every engagement is hourly time & materials with senior US engineers — as a bounded project or as staff augmentation inside your team. Before work starts we agree scope, staffing, and timeline in an initial conversation, and we revisit them openly whenever the facts change. No fixed-price packages, no surprise change orders: you see the hours and what they bought.

Baselines before novelty

The first modeling artifact in any project is a simple, honestly-evaluated baseline. Every subsequent idea — a bigger backbone, a new augmentation, a different loss — is a controlled comparison against it, with fixed seeds and recorded runs. Improvements we cannot measure are improvements we do not claim.

Data before architecture

In applied work, split hygiene, label quality, and input-pipeline health decide more outcomes than model choice. We look there first, and we will tell you plainly when the highest-value next step is better data rather than more modeling hours.

Reproducibility is the deliverable

Training runs are scripted, seeded, and recorded. When an engagement ends, your team can retrain the model from the repository and reproduce the reported numbers. Notebooks are for exploration; deliverables are code.

Verification at every hand-off

Migrated code reproduces the old system before the old system is retired. Converted models pass parity tests before they ship. Deployed models carry monitoring before they take traffic. Each hand-off has an explicit check, agreed in advance.

Your stack, your environment

We work inside your repositories, your cloud accounts, and your security boundaries. Code and data stay in your environment, and everything we write belongs to you.