AI Agents & Automation in Tamil Nadu

Usually, and it is the normal starting point rather than an obstacle. The important design decision is what happens when the agent is unsure — flagging for review is almost always better than guessing, because a confident wrong entry in a system of record costs more than a gap someone fills in.

As little as possible, and that is a design constraint rather than an afterthought. Systems that require people to record things differently get abandoned within months. It is cheaper to build software that reads what is already produced than to retrain a process that works.

A chatbot answers. An agent acts — it calls tools, queries systems, and completes multi-step tasks with defined boundaries. If the value is 'it tells the user something', you want a chatbot. If it is 'it does something on the user's behalf', you want an agent.

It depends on the task, and the honest answer is that you should be able to switch. Route simple classification to a small fast model and reserve a frontier model for reasoning-heavy steps. Building against an abstraction rather than one vendor's SDK keeps that option open.