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AI Agent Development

Your next hire doesn’t need a desk

AI agent development that takes over real jobs inside your business. Built on your data and your infrastructure.

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Prefer to talk? Call +971 55 414 1234

The stack we build on

Models

AnthropicGoogle Gemini

Agent protocol

Model Context Protocol

Built in

TypeScript

Runs on

Next.jsVercel

Memory

PostgreSQLSupabase

They read your systems. They decide. They act. They report back.

The short version

An agent is software that finishes a job on its own: it reads the situation, decides, acts, and tells you what it did. A chatbot answers questions. An agent closes the loop.

We build yours around a brain: a knowledge base of your business that the agent reads before acting and writes back to after. That is the difference between an agent that stays generic and one built to get sharper the longer it works for you.

That is what an AI agent development company should mean in practice, and it is the same work behind the nine brains on our Build page. Every engagement leaves you with the agent, the keys, and a brain licensed to your business.

Agents we build

Every one of these is scoped to a job you can name. These are the patterns we reach for most.

24/7

It never clocks off

An agent works the night shift, the weekend, and the public holiday. The job gets done at 3am because nobody had to be awake for it.

01

Operations agents

The weekly process your team does by hand: reconciliations, data moves between systems, order handling, follow-ups.

02

Support and sales agents

Answer on your site and WhatsApp with your real inventory, prices, and policies. Escalate to a human the moment it matters.

03

Marketing agents

Research, draft, schedule, measure, adjust. Channels run against a strategy instead of one-off posts.

04

Research agents

Watch markets, competitors, and prices on a schedule. Findings arrive as decisions you can act on that day.

05

Reporting agents

The weekly numbers, written and sent without anyone assembling a spreadsheet at 11pm on Sunday.

06

Custom agents

The job only your business has. If a competent person could do it with your systems and a written procedure, an agent is a candidate.

1 approval

A human stays in the loop

The agent proposes, you approve. It runs in draft mode until its output earns the handover, and on the work that matters it stays there for good. Every action is logged, the approval gates are yours, and a correction you make once sticks. The failure mode is a caught mistake, not a silent one.

9,000+

It plugs into what you already run

Your agent gets hands. Through Zapier MCP it can act in over 9,000 apps, so it works your inbox, your CRM, your sheets and your schedulers the way your team does. If a tool has an API, it is reachable.

  • Gmail
  • HubSpot
  • Zoho
  • Hootsuite
  • MailChimp
  • Notion
  • Shopify
  • and 9,000 more

How it works

It starts with watching one person work, and it does not stop there.

01

We watch the job

We sit with whoever does it now and watch them do it for real, on real work. The rules that matter are the ones nobody ever wrote down: the awkward exception, the customer you handle differently, the thing that must never happen. We write those down.

02

We build it on your stack

The agent runs on your cloud, with your keys, on your data. It gets a brain that holds your rules, your tone, and everything it has seen so far. Before it touches anything, we set what it may do on its own and what has to come to you first.

03

It runs in draft

It does the real job next to your team, writing what it would send instead of sending it. You see every action it takes and you approve it, or you don't. It gets the handover when the drafts stop needing your edits, not before.

04

You take it over

The agent and the code are yours. The brain stays licensed to your business and keeps working for you. Every run writes back into it, so the version running next month knows more than the one running today.

Why ours keep getting better

Most agents are built stateless: every task starts from zero, and the tenth week is no better than the first. Ours are built around a brain, a living knowledge base of your business that every run reads from and writes back to.

When the agent handles an edge case, the brain remembers. When you correct it once, it stays corrected. That compounding is the whole point, and it is why we build the brain before we build the agent.

Meet the Nine Brains

Questions, answered

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

A chatbot converses; an agent completes. A chatbot answers a question about your refund policy. An agent checks the order, applies the policy, issues the refund, logs it, and messages the customer. We build chatbots too, but most businesses that ask for one actually need the agent behind it.

How much does AI agent development cost?

Agent builds fall under our Build tiers, which start from $2,500 one-time. The Growth Partner retainer covers the run, upkeep and improvement at an introductory $1,250 per month, which renews at $2,500 per month. The honest answer is that scope drives it: one well-defined job costs less than an agent that touches five systems. The build call is where we put a real number on your case.

How long until an agent is doing real work?

Mapping the job takes a few days. A first working agent on a well-defined job typically runs in draft mode within a few weeks, and earns full handover when its output holds up next to your team's. Complex multi-system agents take longer, and we will say so upfront.

Do we own the agent, or do you?

The agent and the code are yours, running on infrastructure in your name, and they keep working if we ever part ways. The brain has a split: its structure is licensed to you and stays ours, exactly as our pricing page states, but what you put into it and everything it learns about your business are yours. No lock-in on anything that runs in your name.

What does the agent learn from, and where does our data go?

The agent works from your systems and its brain, which lives with you. We do not pool client data, we do not train shared models on it, and one client's brain never feeds another's. The same rule we publish in our privacy policy applies to agent work.

What happens when the agent gets something wrong?

It will, occasionally, like any new hire. That is why guardrails are step one: draft mode for anything consequential, approval gates you control, full logs of every action, and corrections that stick because the brain remembers them. The failure mode is a caught mistake, not a silent one.

Everything else we do

The full catalog on the Build page

Start with the job that eats your week.

Prefer to talk? Call +971 55 414 1234