AI Agent Development

A custom agent that does the work, not a chatbot that only answers

A chatbot answers and forgets you.

A rule repeats until an exception breaks it. An AI agent reasons over a goal and acts on its own. dotfun's AI agent development services build that agent for you, wired into the tools your team already runs.

LET’S CHAT

You do not need another bot.

You need something that does the job.

Most teams already tried the easy version, and it did not hold.

The chatbot only talks.

It answers a scripted question and stops. Ask it to update a record, and it cannot.

A conversation, not a worker.

The simple automation breaks on the exception.

A fixed if-this-then-that rule works until the input changes, then it stalls quietly. Rules do not reason.

They repeat.

The DIY platform sits unused. 

Building the agent turns out to be a real project nobody has time for. 

The license renews; the agent never ships.

The offshore build does not fit.

You handed a spec to a staff-aug shop and got code that runs

But does not understand how your business works.

You do not want a toolkit.

You want the thing built, wired in, and working — and that is what our AI agent development services exist to do.

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What you get from dotfun's AI agent development services

A custom agent that reasons over a goal and acts inside your stack. Done for you, senior-led, and wired to the funnel so the work shows up in pipeline.

It reasons over a goal, not a script

A custom agent is given an outcome, not a decision tree. Tell it to "qualify this inbound lead and book the next step," and it reads the context, works out the steps, and knows when to ask a person (IBM and Google Cloud define an agent the same way).

It works inside the tools you already run

An agent that lives in a demo is useless. We build agents that read from and write to your CRM, helpdesk, and database. The wiring is the hard part, and the wiring is what we do.

It handles the variation a rule cannot

Real work is messy. Inputs vary and edge cases show up daily, and a rule stalls on all of it. An agent reads the situation, adapts, and either finishes the task or escalates it cleanly.

It is built for you, not handed to you

This is not a platform where you assemble the agent yourself. Our senior team scopes, builds, grounds, tests, and ships it. You do not need an in-house AI engineer to run it.

The work AI agents for business actually take off your team

Capability examples: repetitive, judgment-light work that still needs to read context and act.

Support triage and first response

Reads a ticket, pulls the account context, drafts a first reply, routes the hard ones to a person.

CRM hygiene and enrichment

Dedupes, fills gaps, updates stages, flags what looks off.

Lead qualification and routing

Reads an inbound lead, asks the qualifying questions, routes it to the right owner.

Research and draft 

Gathers what is scattered across your tools and drafts the reply or brief a human approves.

Internal operations

Reconciliation, status updates, handoffs between systems.

How dotfun builds a custom AI agent, start to finish

No black box — the path from a workflow that hurts to a working agent you own.

1
Scope the job.
We start with the workflow, not the technology:

Which task, what inputs, and where a human stays in the loop. If a custom build is not the right answer, we say so — sometimes the AI Audit or a productized Iris option fits better.

2
Ground it in your data.
An agent is only as accurate as what it knows.

We connect it to your real sources so its answers come from your business, not a general guess.

3
Wire it into your stack.
We need title here to maintain consistency

We build the connections into your CRM, helpdesk, and tools so the agent reads and writes where the work lives.

4
Test before it ships.
We need title here to maintain consistency

Before an agent touches a live customer or a real record, we test it against real cases and set the escalation rules.

5
Maintain and improve it.
We need title here to maintain consistency

We watch how it performs, correct what drifts, and extend it as the work changes. You own it.

If the build-vs-buy question is still open:

Take the free iris by dotfun AI Maturity Assessment: 15 minutes, conversational, and you get a written action plan within the hour, plus an optional 30-minute walkthrough. No credit card required.

TAKE THE ASSESSMENT

How we keep a custom agent accurate

No AI system is perfect, and any team that promises zero mistakes is selling you something. A serious build engineers the risk down four ways.

Grounding

The agent acts from your data and rules, not open-ended guessing. The biggest single lever on accuracy.

Scope limits

A tight agent that does one job well beats a broad one that improvises.

Human escalation

When the agent is unsure or hits something outside its lane, it does not fake an answer. It hands off to a person with the context.

Evaluation

We test against real cases before launch and keep checking after.

We call this an approach, not a guarantee. The controls are built in from the start, and we are straight about the edges.

Why a done-for-you build beats the alternatives

Compared to a chatbot or a simple automation:

A chatbot answers; an automation repeats a fixed rule until an exception breaks it. An agent reads context, decides, and acts inside the systems where the work happens. Use the simpler tools for fixed, answer-only tasks; use an agent when the work needs judgment.

Compared to a DIY agent platform:

Build-your-own-agent platforms hand you the tools and leave the build, grounding, integration, and upkeep to you. dotfun hands you a working agent instead of a toolkit and a to-do list.

Compared to an offshore staff-aug shop:

Handing a spec offshore gets you code that runs but often does not understand your business. dotfun is the same senior team that runs growth and operations for our clients, so people who understand the funnel build the agent that plugs into it.

DON’T WORRY

The parts teams worry about, handled

You own the agent and the data.

The workflows, the logic, and the data it runs on belong to your business, not to a platform you rent.

It ships wired into your stack.

We do the integration work so the agent reads and writes inside your tools from day one.

It stays in its lane.

The agent does what you scoped it to do and escalates the rest to a person, rather than improvising outside its bounds.

It grows with you.

We maintain it, correct what drifts, and extend it as your workflow changes, so it keeps earning.

Iris or a custom agent — which one do you need?

dotfun builds both, so we can be honest about the split.

Iris is our productized AI growth platform — a ready-to-run system with an AI receptionist, voice, SMS, calendar, web chat, and an AI CRM you switch on. A custom agent is our bespoke work — built around your specific stack, data, and workflow, for a problem no packaged product covers.

Choose Iris when a proven front-desk and growth-automation system fits; choose a custom build when the work is specific to your business. Not sure which side you are on? The AI Audit diagnoses which path pays back before you commit.

Agent development sits in dotfun's AI Solutions wing, alongside AI software development and workflow automation — for when a job needs an app or process built, not an agent.

Built by dotfun.

Our agent is built by Run Good

the same senior engineers who run automation for dotfun's growth clients every day. They bring 30-plus combined years in B2B tech and software builds to your workflow.

And because that team sits next to our growth and design work, an agent ships wired to the funnel and the tracking, so the work it does shows up in pipeline — not just in a log. That is the edge our AI agent development services carry that a standalone dev shop cannot.

Frequently asked questions

What is the difference between an AI agent and a chatbot?

A chatbot answers. An agent reasons over a goal and takes action: it works inside the tools you already run, decides what to do next, and finishes the job instead of handing it back to a person.

How is an agent different from workflow automation?

An agent is one autonomous worker with a goal. Workflow automation orchestrates a multi-step process across your stack. Plenty of builds use both, and we scope which one your problem actually needs before anything gets built.

Do we get a toolkit or a finished agent?

A finished agent, built for you rather than handed to you. You are not buying a platform to learn and staff. We scope the job, build it against your real data and edge cases, and hand over something that runs.

How do you keep a custom agent accurate?

Four ways: grounding it in your own data, setting hard scope limits on what it may do, routing anything uncertain to a person with the full context, and running an evaluation set it has to clear. No agent is perfect, and any team promising zero mistakes is selling you something. The work is engineering the risk down.

What kind of work does an agent take off the team?

The repeat work that needs judgment but not a person: support and customer success queues, RevOps execution, and the cross-tool steps someone currently carries by hand. It is built for B2B operators whose workflow does not fit an off-the-shelf product.

Should we build a custom agent or adopt Iris?

If the problem is front-desk and speed-to-lead work, inbound calls, follow-up, leads that never get logged, Iris covers it and works on day one. Build custom when the workflow is specific to your business or spans your own tools. If that is still open, the free Iris by dotfun AI Maturity Assessment is a 15-minute way to settle it.

Who a custom AI agent is built for

Our AI agent development services fit teams with a specific, repetitive workflow a packaged product does not cover.

B2B operators with a workflow that does not fit a product

You have a process specific to how your business runs, and no off-the-shelf tool matches it. A custom agent is built around your workflow, not someone else's.

Support and CS teams drowning in repeat work

Your team spends the day on triage, routing, and first responses that follow a pattern. An agent takes that front layer so your people handle the cases that need judgment.

RevOps and growth teams who need clean, fast execution

You need leads qualified and routed, records kept clean, and follow-up that does not wait on someone remembering. An agent runs that layer so speed-to-lead stops depending on who is watching.

Founders who want it done, not DIY

You know an agent could take real work off the team, but you do not want to become an AI shop to get it. dotfun builds it and maintains it.