The model provider is the most visible AI decision, so it gets too much attention. In support chat, the harder question is what the assistant is allowed to do. Can it answer from the knowledge base? Can it draft a reply but wait for an operator? Can it close a conversation? When should it stop and hand over? A fast model with bad rules will still create bad support.
What each provider is good for
OpenAI is a practical default for common support questions. It is fast, familiar to many teams, and works well for short answers, FAQ-style requests, and product questions with clear documentation. Anthropic is often a better fit when the conversation is longer or the tone needs more restraint. Ollama is different: you run the model yourself, accept the operations work, and keep calls inside your own environment.
Convor uses a BYOK approach. The organization connects its own provider credentials, and the server resolves the configured provider at request time. That gives teams room to start simple and change later. You can validate the workflow with a hosted model, then move sensitive use cases to a self-hosted setup if privacy or procurement requires it.
Ground the answer or do not answer
Support AI should not be creative in the way a writing assistant is creative. It should be boringly accurate. The useful answer is the one based on your documentation, known product behavior, plan limits, integration rules, and the current conversation. If the knowledge base does not contain the answer, the assistant should say that or hand off. Guessing politely is still guessing.
That is why Convor connects AI to knowledge-base content and conversation context. The model can draft a reply, but the surrounding product decides what material it sees, how much history is included, and whether an operator needs to approve the result. The model matters. The wrapper around it matters just as much.
Track cost before it surprises you
AI cost usually grows quietly. One feature summarizes conversations. Another suggests replies. A third translates messages. Then auto-responses run during a traffic spike. If usage is not tracked inside the product, the provider invoice becomes the first warning. Convor records AI usage so teams can compare cost with outcomes instead of treating every generated reply as a win.
Handoff is part of the AI feature
Billing disputes, account access problems, angry customers, legal requests, and unclear bugs should move to a person quickly. The assistant can still help by collecting context and writing a summary for the operator. It should not pretend to have authority it does not have. Teams trust AI more when it knows where the boundary is.
Pick the provider after you define the workflow. For support, that order saves more trouble than any benchmark table.
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