When your process needs a tailored prediction model.

If you or a research partner already have a model, start with integration into NAZARE. If a new model is needed, scope quality prediction, anomaly detection or recommendations as a separate development project with agreed evaluation data. Distinguish platform supply, model development, system integration and operational support.

Ingkle focuses on the manufacturing AI data platform. NAZARE supplies data and model-operation foundations; NAVIS uses knowledge and tools. Specialized ML development is an optional, separately scoped engagement.

Existing in-house or partner models can be reviewed for data and serving integration.

1. Is the prediction tied to a concrete decision?
2. Are there verifiable outcomes and representative cases?
3. Can an owner act on the result?
4. Can evaluation cover time and product variation?

Start with preparation or exploration when labels or rare-event examples are missing.

Define inputs, features, training/evaluation separation, versions, inference latency and output storage. Collect drift and false/missed cases in operation and agree re-evaluation criteria, including actionability.

Separate preparation, model/code, evaluation, deployment, handover and maintenance. Agree data rights, model delivery/ownership and retraining in the contract. Application scenarios do not guarantee model or business outcomes.