Frontier Engineering / Fine-tuning and your own models
Your own models, kept only when they beat what you use today.
Models adapted to your domain, from embeddings, rerankers and classifiers to judgment models, with dataset review, evaluation design and deployment guidance.
- Examples
- Adapt
- Held-out eval
- Keep winner
People and evidence stay in the flow
Problems we solve
- A general model falls short on the task your business needs done.
- Without evaluations, nobody can tell whether a new model is better.
What you own at the end
- Your own models, in your account.
- The evaluations that decided what shipped.
What we deliver
Embeddings, rerankers and classifiers
Judgment models
Dataset review and evaluation design
Your own models, trained on your team's work and kept only when they win on held-out past work.
Deployment guidance
How an engagement runs
Assess
We start from the outcome, the constraints and the evidence your team needs, and scope the delivery team, milestones and commercial terms with you.
What we ask first:
- Which task or domain should the model handle, and where does the current approach fall short?
- What representative examples are available, and what permissions or privacy requirements apply to that data?
- Which evaluation goals matter: task accuracy, consistency, latency or another measurable outcome?
- Are there model, deployment or integration constraints that the engagement must account for?
Build under controls and evals
Work ships under governance controls and evaluations, with a human approving what matters.
Run and improve
We stay accountable after go-live and keep improving what we built together.
Related product
Tillerpin
A System-1 model for fast, typed decisions (yes/no, choice and relations), designed for calibrated decision-making in agent pipelines, with open weights and documented training data. Coming soon.
Frequently asked questions
Do you promise an accuracy improvement?
No. Supported model families, the evaluation approach and the delivery scope are agreed with your team, and evaluations decide what ships.
What data do you need?
Representative examples of the task, with the permissions and privacy requirements that apply to that data.
Do you publish prices?
No. Scope, the delivery team, milestones and commercial terms are agreed with you.
Can my AI assistant read this page?
Yes. This page is ordinary HTML that needs no AI call, and it is also served as Markdown. Your assistant can read the published catalog or connect through F200.ai’s MCP interface and retrieve this offering by its stable identifier: service.fine-tuning.
Start with the problem.
We’ll start with a conversation.