AI Models
Define the domain, source boundaries, information objects, labels, evaluation samples, review paths, and operational limits before a model is trained, prompted, or connected to a product.
Specialized AI starts with domain definition. OCO identifies the data field, vocabulary, labels, source limits, prohibited uses, expected questions, evaluation samples, and user roles before selecting or building a model layer. This prevents the model from becoming a generic chatbot attached to sensitive data and keeps the AI tied to the purpose of the product.
Approach
The model is never treated as the whole product. OCO first defines data boundaries, source quality, test sets, evaluation paths, human accountability, audit records, prompt controls, output controls, error handling, and deterministic software around the model. Only then can the model become a commercial or operational layer. This approach keeps AI useful without letting it erase the distinction between source data, model interpretation, human review, approved conclusions, and actions taken outside the system.
Scope
OCO builds specialized AI models when ordinary querying is not enough: classification, reasoning, anomaly detection, explanation, and operational support are tied to an approved data purpose.
Specialized AI Models for organized data.
AI model output is used as assistance, not authority. Human accountability, approved use, data boundaries, and system-specific constraints define how model results are handled.