One place to build
your decision model.

Start with what you know.

Connect Attio, Pylon, or Fireflies. Turn records into examples that pair the information available at the time with the outcome that followed. Review those examples before training.

Fireflies

Train on examples. Test separately.

Post-train Kev 4B for your decision task. Track validation metrics as it trains. Keep a holdout set outside the training process and export it for independent evaluation.

Reviewed examples

• TrainingLearn patterns
• ValidationTune the model
• HoldoutEvaluate independently

Put the model to work.

Use a deployed version in the app, a workflow, or through the API. Get a yes/no probability, a category, or a score for the task you trained it on. Trace each result to its model version and inputs.

Keep learning from new outcomes.

Schedule data refreshes and retraining. Review each candidate before deployment, with previous versions available for comparison. A training run does not automatically replace the live model.

Initial training and deployment need setup support. Automatic holdout evaluation and model promotion are planned.