AI Agent Examples 2026: Six We Built and Run

Most explanations of AI agents stop at the definition, which is why the term still sounds like a category rather than a thing you could point at. The AI agent examples below are the six we built and sell. Each one is a single job that used to sit with a person, and reading them in a row says more about what an agent is than another definition would.

What makes these agents rather than tools

A tool executes what somebody wrote down. An agent works out what to do with the case in front of it, inside limits somebody set, and hands back the cases it could not settle.

AI agent examples are more useful than definitions for exactly that reason: a definition can be agreed with and still leave you unable to name one. We covered the line between the two (opens in new tab) separately, so here it matters only as a test: if the job could be written as a fixed rule, what you want is a script, and it will be cheaper. Everything below exists because the input arrives in a shape no rule anticipated.

Six AI agent examples, and what each one does

Invoice collection agent. Chases what customers owe you, so the only thing you look at is what is still missing. Collections is a job of repeated, slightly different reminders sent at the right moment, which is the shape of work an agent handles well and a rule handles badly.

Marketing agent. Connects ads, website and CRM, shows what is working, and turns that answer into the next action. Anyone who has tried to reconcile those three sources knows that the hard part is agreeing what counted as a result in the first place.

Public procurement screening agent. Finds the tender that fits, messages you about it, and helps decide whether to bid. Screening is a reading job with a deadline attached, and the decision to bid stays with a person, because it depends on free capacity rather than on the notice.

MygomSEO. One agent across SEO, content and social, instead of a tool for each and a person stitching the three together. The three jobs share the same source material, which is the argument for one agent rather than three, and the reason most companies end up with three anyway is that the tools were bought one at a time.

AI Business Brain. The layer the rest sit on, described below.

DAVE. Still in beta, and the odd one out: it coordinates coding agents, breaks delivery into pieces and returns a testable build. It belongs to software delivery rather than to the operations work the other five handle.

What holds them together

An agent that reaches real systems is only as sensible as the answer to who is allowed to run it, and what it is allowed to know. That is the part the individual descriptions above leave out.

AI Business Brain (opens in new tab) is our answer to it. It connects the tools a company already uses, CRM, email, documents, projects, calendars and chats, and keeps track of decisions, commitments and risks across them. Our own team runs on it. Separate agents are coordinated through it with defined rights, and decisions of any weight wait for a person to approve them. This is our own product, so read the paragraph with that in mind.

The access question is also a legal one. The EU AI Act requires providers and deployers to take measures to support the development of AI literacy (opens in new tab) among their staff and others operating AI systems on their behalf. No particular level is demanded of any individual, and the obligation still lands on a company where everybody is running agents against live data.

Which of these touches your area

Our diagnostic looks at six areas of a company: documents and invoices, reports and KPIs, customer communication, internal operations, sales, and production and pricing.

Reading the six agents above against that list is worth doing, because the match is rarely one to one. An agent built for one job often reaches into two areas, and an area where nothing on the shelf fits simply means the work would be built rather than bought.

Most AI agent examples you will read are presented as a complete set covering everything. Treat any such list, including this one, as a starting point for naming your own job rather than as a menu to choose from.

What a product page cannot tell you

It shows the finished answer, not the queue. Every agent here returns work it could not complete. The page does not say who opens that queue in your company, and that question decides more than the feature list does.

Six agents exist because six problems repeated at our scale. A company with different work would end up with a different six, and copying ours is the wrong exercise.

Most companies should not start with an agent at all. For the first problem a company names, the cheaper fix is often an integration or a changed habit. We say that during the audit even though the agent is the thing we sell, because the alternative is a project that underdelivers for a year without anybody calling it off.

Where to start

Pick the job in your week that comes round most often and has the fewest exceptions. Write down what arrives at its start, what leaves at its end, and who currently decides the things in the middle.

That description is enough to tell whether any of the six AI agent examples above would fit, or whether what you need is a script, an integration, or nothing at all.

Writing it down also settles an argument that otherwise runs for weeks, because the disagreement is usually about who decides the middle part rather than about the technology.

Get in touch (opens in new tab) and bring that one job with you. We will help you work out where to start, and whether it is worth starting at all.