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An AI agent for your business tasks

If your task goes beyond answering questions and involves checking information, using tools and following up, an agent may help. We’ll start with one clear task and define its access.

How is an agent different from a chatbot?

A chatbot mainly talks and answers. With the right tools and access, an agent can move through several steps: read the situation, perform an allowed action, then check and report the result. That authority needs clear limits from the start.

AgentBot, which I built for my own projects, takes a request in Telegram and handles investigation, changes and follow-up in the same conversation. You can explore that example; your tools and scope would be defined separately.

Which task should we start with?

Choose a task with clear inputs, outputs and a definition of done. It might gather information, check a service or prepare a report for approval. If the workflow is still unclear, we’ll sort it out first.

We’ll need a real example, the tools you use and the mistakes that matter to you. Not every task needs an agent. If straightforward automation gets the same result, that’s what I’ll suggest.

How do permissions and approval work?

We’ll define what the agent can only read, what it can change and where it needs your approval. Access is limited to the task, and credentials belong on the server. The details depend on your tools and the sensitivity of the work.

We’ll plan reporting, error checks and how to stop further work. Stopping an agent doesn’t necessarily undo earlier changes. Tasks that need rollback should have a rollback method and owner agreed in advance.

What do building and cost involve?

We’ll write down the scope and success criteria, build a limited version and test it on real examples. Tools, decision complexity, approvals, usage and support affect time and cost. Model and infrastructure costs are also made clear separately.

Explore the work I’ve built

Questions you might have

Can an agent do everything in the company?

No. Each agent depends on its tools, access and agreed scope. We start with a task we can evaluate, then decide whether to expand it.

Does every step need a language model?

No. Fixed calculations and rules usually belong in code or defined workflows. A model helps where understanding text or choosing a path is useful.

Do you have a working example?

I built AgentBot for my own website, bot and server tasks. Its case study shows conversations, checks and actions.

A little reading before you decide

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Let’s start with a real example

I’m Milad Sadeghi, founder of SmartFlowX. I build bots, agents and automation for businesses in Iran. In our free first conversation, we’ll look at your work and find a suitable starting point.

Let’s talk about my business
Let’s talk Telegram