Agency · ChatGPT · OpenAI

The ChatGPT agency.ChatGPT, put to real work.

ChatGPT promises to change how your team works, then hands you a blank chat that guesses at your business. We build the Workspace Agents, custom GPTs and OpenAI-API automations for the workflows you repeat, ground them on your data with RAG, and roll it out with permissions.

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★★★★★Verified Trustpilot reviews · AI, automation & growth agency

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What we do

A ChatGPT agency builds you systems, not a login.

Anyone can buy the seats. Building agents around your real workflows, grounding them on your data, and rolling it out with permissions is a different job. Here are the four things we own.

Method · 4 stages

We build with ChatGPT like a system, not a gadget.

Most ChatGPT rollouts die the same way: a demo that wowed the room, then a tab nobody opens because it guessed at the business and there was no real workflow behind it. So we treat it like infrastructure: agents built for real tasks, grounded on your data, wired into the stack, handed to a team that knows how to run it safely.

  • Audit · map your real workflows, your data, and where ChatGPT helps or doesn't
  • Build · the agents, GPTs and API automations for the tasks you actually repeat
  • Ground · RAG on your data so answers are sourced, not hallucinated
  • Rollout · permissions, prompt library, training and AI ops your team runs without us
Walk me through the method
Differentiator · no badge

An automation agency, not a seat reseller.

We don't sell an OpenAI partner tier. We come from automation and AI, so we see ChatGPT for what it is: a strong engine that has to plug into the rest of your stack and stay governed. That's exactly what's missing when a rollout ends at a chat tab with no workflow, no grounding and no permissions.

  • We come from automation and AI, not from reselling seats. ChatGPT is a node in your stack, not the whole point.
  • Model-agnostic: we build on ChatGPT/OpenAI when it fits, and we'll say honestly when Claude or an open model fits a task better.
  • We care about governance (data, permissions) not just a flashy demo. A leak or a hallucination costs more than a slick screen recording.
  • No partner badge to wave. We're judged on whether the agents ship and get used, not on a tier.
Show me a typical build
What we build

ChatGPT at the center, your real workflows around it.

We build the parts that do real work, then connect them to the tools your team already uses. Here's what a real build covers.

  • Build

    Workspace Agents

    We build the Codex-powered agents OpenAI is rolling out to replace custom GPTs: cloud-run, shareable across the org, plugged into tools like Slack and Salesforce, scoped to a repeatable workflow your team runs every week.

  • Build

    Custom GPTs

    Where a focused GPT still fits, we build it: a tuned system prompt, your reference docs attached, the guardrails set, so a specific task is one click instead of a fresh prompt every time someone reinvents it.

  • Build

    OpenAI API automations

    We wire the OpenAI API into your stack and orchestrate it through n8n or Make: drafting, classification, extraction and summaries run on a trigger, with a human approval step where it matters, not a black box.

  • Build

    RAG assistants on your data

    We ground ChatGPT on your docs, wiki and tickets so answers cite a source instead of guessing. Retrieval, chunking and the prompt are set up so the assistant stays accurate as your knowledge base grows.

  • Build

    Team rollout & permissions

    ChatGPT Business or Enterprise set up with org permissions, data controls and the right plan per team. People get access to what they need, sensitive data stays out of public chats.

  • Build

    Prompt libraries & guardrails

    A shared library of prompts that actually work for your team, plus the guardrails: what's safe to paste, what isn't, where outputs need a human check. The tool gets used right instead of misused fast.

Free audit · 60 minutes

We map your workflows, you leave with a plan.

Before quoting anything, we take 60 minutes to look at your real workflows, your data and where ChatGPT would actually move the needle. You leave with an honest read on what to build first, what to ground on your data, and what isn't worth automating yet. Zero pitch, just an operator's take on your AI stack.

  • An honest read on whether ChatGPT fits the workflow
  • The agents and automations to build first
  • How to ground answers on your own data
  • A frank take on when Claude or an open model fits better

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Or send your brief instead
Our approach

How we run a ChatGPT build.

Five steps, in order. We don't scale before answers are sourced, we don't hand over an agent nobody can run, and your team owns it at the end. Each step has a deliverable and you sign off before we move on.

  1. Step 1 · Workflow & data audit

    Map where ChatGPT actually helps

    We sit down with the people who'd use it day to day, ops, support, sales, marketing, and look at what's repetitive enough to automate: the report nobody wants to write, the research that eats an afternoon, the triage that piles up. We check what data the model would need and how sensitive it is. You leave with a clear read on where ChatGPT helps, where it doesn't, and where Claude or an open model would fit better.

  2. Step 2 · Build the agents

    Build the Workspace Agents and GPTs

    We build the Workspace Agents and custom GPTs around the workflows from the audit, scoped tight so each one does a real job well. Since OpenAI is phasing out custom GPTs in favor of Codex-powered Workspace Agents, we build for where the platform is heading. An operator on your side signs off on the output before we wire anything to your tools.

  3. Step 3 · Ground on your data

    Wire in RAG so answers are sourced

    We connect the assistant to your docs, wiki and tickets with RAG so replies cite a source instead of guessing. We set up retrieval, chunking and the prompt so it stays accurate as the knowledge base grows. The goal is an assistant your team trusts because every answer points to where it came from, not a confident paragraph nobody can check.

  4. Step 4 · Integrate & automate

    Wire OpenAI into the rest of your stack

    We wire the OpenAI API into your apps and automate the busywork through n8n, Make or directly: drafting, classification and summaries run on a trigger, with a human approval step where it matters. The model does the work inside the tools your team already uses. Every flow ships with its error handling and a fallback, not bolted on later.

  5. Step 5 · Roll out & hand over

    Your team runs it, you don't need us

    We set up ChatGPT Business or Enterprise with the right permissions and data controls, hand over a prompt library, and train the people who'll own it: what's safe to paste, when to trust an output, when to check it. The build ships with a short playbook and basic AI ops so you can see what's running. If you want us on call for what scales next, we talk about that separately.

Proof · what the teams say

We're judged on the agents that get used.

No partner badge to display, so we lead with what matters: feedback from the teams whose ChatGPT stack we built, and whether it kept getting used after we left. Our Trustpilot reviews come from those operators, not from a marketing deck.

  • The build ships with a prompt library your team can run
  • Answers grounded on your data, sourced before we scale
  • Agents wired into the stack, not stuck in a chat tab
  • Trustpilot reviews come from the teams we built for
Talk to the team
FAQ · ChatGPT agency 2026

The questions we get asked on repeat.

  • What does a ChatGPT agency actually do?
    A ChatGPT agency builds with ChatGPT and the OpenAI API for your business, instead of leaving you with a blank chat and a vague promise. We build Workspace Agents and custom GPTs for your real workflows, wire the OpenAI API into your stack through n8n or Make, ground answers on your own data with RAG, and roll out ChatGPT Business or Enterprise with proper permissions. The point is repeatable work the model handles reliably, not a tab everyone opens twice and forgets.
  • How much does it cost to build with you?
    It depends on scope: how many agents or GPTs, whether you need RAG on your data, how deep the API automation goes, whether it's a full Business or Enterprise rollout with governance. A single custom GPT is nothing like a fleet of Workspace Agents wired into your CRM with a knowledge base behind them. We don't throw out a flat package. We start with a free 60-minute audit to frame the need, then quote a fixed scope. The ChatGPT or OpenAI plan itself you buy from them directly.
  • Workspace Agents or custom GPTs: which do we need?
    Increasingly Workspace Agents. They're the evolution of custom GPTs, powered by Codex, they run in the cloud, can be shared across your org, and plug into tools like Slack and Salesforce. OpenAI is phasing out custom GPTs in favor of them, so for anything new and shared we build agents. A custom GPT still fits for a simple, self-contained task on one person's desk. We'll tell you which one your workflow actually needs during the audit.
  • Can ChatGPT answer from our own data without making things up?
    Yes, that's what RAG is for. Out of the box the model guesses, and a confident wrong answer is worse than no answer. We ground it on your docs, wiki and tickets so each reply cites a source. We set up retrieval and chunking so it stays accurate as your knowledge base grows. It won't be perfect on every edge case, and we'll be honest about where it still needs a human check, but for sourced answers at scale it holds up.
  • Can you integrate the OpenAI API with the rest of our tools?
    Yes, that's where we add the most value. We wire the OpenAI API into your apps and orchestrate it through n8n, Make or directly, so drafting, classification, extraction and summaries run on a trigger inside the tools you already use. A lead comes in, the model drafts a reply, a human approves, the CRM updates. The model does the work where the work happens instead of you copy-pasting between a chat tab and everything else.
  • ChatGPT or Claude: which should we build on?
    Depends on the task, and we're model-agnostic on purpose. ChatGPT and the OpenAI API are strong for broad workflows, Workspace Agents, and a huge ecosystem of integrations. For some tasks Claude or an open model fits better, and we'll say so instead of forcing one stack. Most teams that work end up with a mix. The point isn't loyalty to a vendor, it's the right model for each job, which is exactly why we don't wave a partner badge.
  • Is ChatGPT Business or Enterprise worth it for us?
    If more than a handful of people use it for work, usually yes. Business and Enterprise give you org permissions, data controls, and the assurance your prompts aren't training a public model, which matters the moment sensitive data is involved. For a solo founder a regular plan is often enough. We'll tell you honestly which plan fits your team during the audit instead of pushing you to the priciest tier by default.
  • Do you train our team or just hand over the build?
    Both, and the training is the point. An agent nobody knows how to use dies after the demo. We train the people who'll own it: how to prompt, what's safe to paste, when to trust an output and when to check it. The build ships with a prompt library and a short playbook, plus basic AI ops so you can see what's running. If you want to go deeper, our ChatGPT training covers the build and the safe-rollout side end to end.
Build with ChatGPT

Stop guessing in a blank chat. Get a system.

A 60-minute audit, your workflows mapped, a build plan that fits your data and your team. If your team can run it in-house after the build, we'll hand you the playbook. If we're the right fit, we handle it.

Book the free 60-min auditSee the agency
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