Your data should not train someone else’s model.
We prefer models that run on infrastructure you control, so costing, vendors, and customer records are not posted to a standard API you cannot audit.
Standard hosted models are convenient. They are also a data-security problem for an operation that does not want its margins, vendor terms, or shop-floor records leaving the building. Where prediction or retrieval helps, we run it locally or on a customer-controlled environment. Some product paths may still call an audited third-party API; we do not pretend otherwise.
As you scale. As volume grows, the local model sees more of your own process — not a generic internet corpus — so answers get more specific to how you actually run.
What this actually is.
Control the endpoint
Costing, vendors, and personal data stay inside an environment you can switch off, inspect, and explain to a board.
Logic first, model second
Workflow, permissions, and records solve the operating problem. Intelligence sits on top where it earns its place.
Answerable under DPDP
What is held, why, who accessed it, and when it is deleted should be retrievable. Software cannot make you “compliant”; it can make the answers available. Not legal advice.