AI agent

What it is

A chatbot answers questions; an AI agent gets things done. It receives a goal in plain language, plans the steps, calls tools — a database query, an API, a spreadsheet, a WhatsApp message — and checks the result before moving on. The language model provides the reading, reasoning and writing; the tools and rules around it decide what it is actually allowed to touch.

In practice a business agent is narrow by design. One agent classifies incoming customer messages and drafts replies for a human to approve. Another reads purchase orders arriving as PDFs and creates draft entries in the ERP. Each has a clear scope, a set of permitted actions, and a point where a person confirms before anything irreversible happens.

Why it matters for a growing business

Much of the work that slows a growing company is unstructured: emails to read, PDFs to re-type, WhatsApp threads to answer, documents to summarise. Classic automation cannot handle that because it needs a fixed format. An agent can read the messy input, extract what matters and hand structured data to the systems that already exist.

The value is not replacing people but removing the copy-and-paste layer between them and their systems. Staff spend their time on exceptions and decisions instead of transcription, and customers get an answer in minutes rather than the next morning.

• Order intake: reading buyer emails or WhatsApp orders and creating draft sales orders
• Support triage: sorting incoming messages, answering routine questions, escalating the rest
• Document handling: extracting data from invoices, delivery notes and forms
• Internal assistants: answering staff questions from policies, prices and stock data

How AutoProbaho uses it

AutoProbaho builds task-specific AI agents that sit on top of a client's ERP, CRM or existing tools, connected through APIs and n8n. Every agent has defined permissions, logs each action it takes, and routes anything uncertain to a human. We start with one narrow, measurable task — usually inbox or order handling — and widen the scope only once the results are trusted.