AI models trained
for your business.
Built on your examples.
Measured against your standards.
Open models.
Your starting point.
Good work starts with the right foundation. Explore open-weight model families, then make one fit your task.
Model selection depends on the task, license, and deployment requirements.
A general model.
A specific job.
We adapt foundation models to the work your team does every day. Start with a defined task, train on approved examples, and test whether the result is better.
Start with the work.
Define the inputs, the expected outputs, and the decisions a person should keep. Gather examples your team has approved.
- Input
- An invoice and its purchase order.
- Expected output
- The mismatched line items, ready for review.
- Human decision
- Approve, reject, or request a correction.
Train for the task.
Choose a foundation model and adapt it using your examples. Confirm licensing, model compatibility, and the path to deployment.
- Foundation modelGeneral capability
- Approved examplesYour task and standards
- Adapted modelReady for evaluation
Make it prove itself.
Use held-out examples to compare the model with your current approach. Review the gains, the tradeoffs, and the cases it gets wrong.
- Task quality Does it get the answer right?
- Cost and latency Does it work at your scale?
- Failure cases When should a person step in?
See the work
behind the model.
Walk through a voice workflow, from selecting data to reviewing an evaluation.
Open the interactive demoA simulation with illustrative data.
to a custom model.
A few answers.
When does custom training make sense?
For repeated tasks with clear examples and measurable outcomes. Prompts and retrieval may already be sufficient; custom training should improve on a strong baseline.
What do we need to begin?
A defined workflow, approved examples, and someone who can judge the results. We agree on the evaluation criteria before training begins.
Can we use our existing infrastructure?
We confirm model licensing, adapter compatibility, and hosting support before choosing a deployment path. The model can work alongside retrieval, business rules, and human review.
How is our data handled?
Before a pilot, we agree on what data is needed, who can access it, where it is processed, and how long it is retained. Your requirements and provider terms determine the approach.