The ChatGPT agency.Deployed safely across your team.
Looking for a ChatGPT agency that does more than hand your team a login? Free ChatGPT and ChatGPT running inside your company are two different tools. We deploy the second: your data kept private, custom agents built around the work you repeat, answers grounded in your own docs, and permissions set so nothing sensitive leaks into a public chat. Automation and AI first, clients worldwide since 2024, no partner badge to sell.
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GeminiA ChatGPT agency deploys a system, not a login.
Anyone can buy the seats. Building agents around the work your team repeats, grounding them on your own data, and rolling it out with real permissions is a different job. Here are the four things we take off your plate.
- Build
Agents and GPTs built around the work you repeat
The seats are easy to buy. A chat tab your team opens twice and forgets is where most of that money goes to die. So we build Workspace Agents and custom GPTs around the jobs people actually redo every week: an account brief before a call, a first draft of the weekly report, ticket triage, a summary of a 40-page contract. OpenAI is now pushing Workspace Agents (Codex-powered assistants that run in the cloud and can be shared across the whole company) over the older custom GPTs, so we build for where the platform is going, not for a feature already on the way out.
See a typical build - API and automation
The OpenAI API wired into the tools you use
A GPT stuck in a browser tab is half a tool. We wire the OpenAI API into your own apps and let the model do the work where the work already happens, orchestrated through n8n or Make (visual automation tools that connect your software without a developer). A lead lands in the CRM, the model drafts the reply, a human approves, the record updates on its own. No more copy-pasting a prompt out of ChatGPT and the answer back into six other tabs.
See the method - Answers from your data
Grounded on your docs, so answers cite a source
Out of the box, ChatGPT guesses. A confident wrong answer about your own business costs you more than no answer at all. We ground it on your docs, wiki and past tickets with RAG (the model reads your files first, then answers from them) so every reply points back to the page it came from. Someone asks a real question about your product and gets a sourced answer they can check, not a plausible paragraph nobody can verify.
See how grounding works - Rollout and governance
Deployed with permissions, not a free-for-all
Turning on ChatGPT Business or Enterprise is step one. The part that protects you is everything after: org permissions and data controls so people reach only what they should, a prompt library the team actually reuses, training so nobody fights the tool, and basic AI ops so you can see what is running. We come from automation and AI, so the rollout is governed from day one, not a free-for-all where a customer list gets pasted into a public chat by accident.
See team rollout
We deploy ChatGPT like infrastructure, not a gadget.
Most ChatGPT rollouts die the same way. A demo wows the room, then the tab goes quiet because it guessed at the business and there was no real workflow behind it. So we treat it as infrastructure instead: agents built for tasks people actually repeat, grounded on your own data, wired into the stack, and handed to a team that knows how to run it safely.
- Audit. We map the workflows your team repeats, the data involved, and where ChatGPT actually helps versus where it does not.
- Build. We ship the agents, GPTs and API automations for those repeated tasks, scoped tight so each one does a real job well.
- Ground. We connect the assistant to your own docs with RAG so answers cite a source instead of making things up.
- Rollout. We set the permissions, hand over a prompt library, train your people, and leave you basic AI ops you run without us.
Free ChatGPT and a deployed rollout are not the same tool.
Your team already opens ChatGPT in a browser. So why pay an agency? Because a private tab and ChatGPT deployed inside your company behave completely differently once real data is involved. Same model underneath, a different level of control. Here is what actually changes when it moves from a personal tab to a governed workspace.
- Your data. On the free plan your prompts can help train a public model. Deployed on Business or Enterprise with our setup, they stay yours and out of any training set.
- Guardrails. A blank tab has none. A deployed rollout has rules on what is safe to paste, where an output needs a human check, and who can reach what.
- A team workspace. Instead of everyone prompting alone in a private tab, agents, prompts and grounded knowledge are shared, so the whole company works off the same tools.
- Confidentiality. Org permissions and data controls mean a customer list or a contract does not end up pasted into a chat window anyone can open.
ChatGPT at the center, the work your team repeats around it.
We build the parts that do real work, then connect them to the tools your team already lives in. Here is what a full ChatGPT build covers.
- Build
Workspace Agents
The Codex-powered assistants OpenAI is rolling out to replace custom GPTs: they run in the cloud, get shared across the company, plug into tools like Slack and Salesforce, and stay scoped to one repeatable job your team runs every week.
- Build
Custom GPTs
Where a focused GPT still fits, we build it: a tuned instruction set, your reference docs attached, the safety rules in place, so a specific task is one click instead of someone rewriting the same prompt from scratch every morning.
- Build
OpenAI API automations
The OpenAI API wired into your stack and orchestrated through n8n or Make. Drafting, sorting, data extraction and summaries run on a trigger, with a human approval step wherever the output actually matters. Not a black box.
- Build
Answers grounded on your data
We connect ChatGPT to your docs, wiki and tickets with RAG so replies cite a source instead of guessing. Retrieval and the prompt are set up so the assistant stays accurate as your knowledge base keeps growing.
- Build
Team rollout and permissions
ChatGPT Business or Enterprise set up with org permissions, data controls and the right plan per team. People reach what they need, and sensitive data stays out of any public chat window.
- Build
Prompt library and guardrails
A shared set of prompts that genuinely work for your team, plus the guardrails: what is safe to paste, what is not, and where an output needs a human to check it before anyone acts on it.
We map your workflows, you leave with a plan.
Before we quote anything, we spend 60 minutes on your real workflows, your data and where ChatGPT would genuinely move the needle. You leave with an honest read on what to build first, what to keep private, and what is not worth automating yet. No pitch, just an operator's take on your AI stack.
- An honest read on whether ChatGPT fits the workflow
- The agents and automations worth building first
- How to ground answers on your own data and keep it private
- A ballpark cost (from $2,000) and a realistic timeline
How we run a ChatGPT deployment.
Five steps, in order, no skipping ahead. Nothing kicks off before the free audit, we do not scale before answers are sourced, and you sign off on the plan and the price before a single hour hits the invoice. Each step has a deliverable, and your team owns the result at the end.
- Step 1 · Free 60-minute audit
We map where ChatGPT actually helps
We start with a free 60-minute audit. We sit with the people who would use it every day, ops, support, sales, marketing, and look at what is repetitive enough to hand off: 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 does not, and where Claude or an open model would fit the job better. No slide deck, no obligation.
- Step 2 · The plan and the price
We agree on what to build, and what it costs
After the audit you get a real quote. It starts from $2,000 and moves with the scope, because a single custom GPT is nothing like a fleet of Workspace Agents wired into your CRM with a knowledge base behind them. We line up what gets built first and put a timeline on it, anywhere from a week to six months depending on the job. The ChatGPT or OpenAI plan itself you buy straight from OpenAI. Nothing gets billed until you have signed off on the plan and the price.
- Step 3 · Build and ground
We build the agents and ground them on your data
We build the Workspace Agents and custom GPTs from the audit, then connect them to your docs, wiki and tickets with RAG so replies cite a source instead of guessing. Since OpenAI is phasing out custom GPTs in favor of Codex-powered Workspace Agents, we build for where the platform is heading. Someone on your side signs off on the output before we wire anything to your live tools.
- Step 4 · Integrate and automate
We wire OpenAI into the rest of your stack
We connect the OpenAI API to your apps and automate the busywork through n8n, Make or directly. Drafting, sorting and summaries run on a trigger, with a human approval step wherever it counts, so the model works inside the tools your team already lives in. Every flow ships with its own error handling and a fallback, built in from the start rather than bolted on when something breaks.
- Step 5 · Roll out and hand over
Your team runs it, with support after delivery
We set up ChatGPT Business or Enterprise with the right permissions and data controls, hand over the prompt library, and train the people who will own it: what is safe to paste, when to trust an output, when to double-check it. The build ships with a short playbook and basic AI ops so you can see what is running. We stay reachable for maintenance and the next round, and if you would rather run the whole thing in-house, that was always the plan.
We are judged on the agents that keep getting used.
No partner badge to display, so we lead with what matters: feedback from the teams whose ChatGPT rollout we built, and whether it was still in daily use months 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, sources cited before we scale
- Agents wired into the stack, not stranded in a chat tab
- Trustpilot reviews come from the teams we built for
ChatGPT for your company, answered straight.
What does a ChatGPT agency actually do?
A ChatGPT agency deploys ChatGPT properly inside your company instead of handing you a login and a vague promise. In practice that means building Workspace Agents and custom GPTs for the work your team repeats, wiring the OpenAI API into your stack through n8n or Make, grounding answers on your own data with RAG so replies cite a source, and rolling out ChatGPT Business or Enterprise with real permissions. The point is repeatable work the model handles reliably, not a tab everyone opens twice and forgets.How much does a ChatGPT agency cost?
It starts from $2,000 and climbs with the scope. A single custom GPT is nothing like a fleet of Workspace Agents wired into your CRM with a knowledge base behind them, so we skip the flat package. After a free 60-minute audit you get a precise quote tied to the actual build, plus a timeline that usually lands between one week and six months. The ChatGPT or OpenAI plan itself you buy straight from OpenAI. We have shipped more than 150 automations since 2024, so the estimate comes from real builds, not a price list pulled out of the air.Are you an OpenAI or ChatGPT partner?
No badge, and that is on purpose. Hack'celeration is an automation and AI agency that builds on ChatGPT and the OpenAI API, not a reseller chasing a partner tier. You buy the ChatGPT Business or Enterprise plan straight from OpenAI, and we build the agents, GPTs and API automations around it. The upside of not being tied to one vendor: when Claude or an open model fits a task better, we say so instead of protecting a logo. You judge us on whether the build ships and keeps getting used, not on a spot in a partner directory.What is the difference between free ChatGPT and ChatGPT deployed in our company?
Four things change. Your data: on the free plan prompts can help train a public model, while a Business or Enterprise rollout keeps them yours and out of any training set. Guardrails: a blank tab has none, a deployed setup has rules on what is safe to paste and where a human has to check the output. A shared workspace: agents, prompts and grounded knowledge sit in one place instead of living in each person's private tab. And confidentiality: org permissions mean a customer list or a contract does not land in a chat window anyone can open. Same underlying model, a completely different level of control.Do you do ChatGPT development, or just setup?
Both, and the development is where most of the value sits. Setup alone is buying seats and switching on permissions, useful but shallow. As a ChatGPT development agency we build against the OpenAI API: custom GPTs, Workspace Agents, assistants grounded on your docs, and automations wired through n8n or Make so the model works inside your CRM, support desk and inbox. A rollout that stops at a chat tab leaves the hard part undone. We build the workflow behind it, ship error handling and a fallback with every flow, and hand your team something they can run without us.Are custom GPTs being deprecated? Should we build Workspace Agents in 2026?
For anything new and shared, yes, build Workspace Agents. They are the evolution of custom GPTs, powered by Codex, they run in the cloud, get shared across the company, and plug into tools like Slack and Salesforce. OpenAI is phasing out custom GPTs in favor of them through 2026, so a fresh custom GPT for a team workflow is building on a feature already on the way out. A custom GPT still fits a simple, self-contained task on one person's desk. We tell you which one your workflow actually needs during the audit.Can ChatGPT answer from our own data without making things up?
Yes, that is what RAG is for. Out of the box the model guesses, and a confident wrong answer is worse than none. We ground it on your docs, wiki and tickets so each reply cites the source it came from, and we set up retrieval so it stays accurate as your knowledge base grows. It will not be flawless on every edge case, and we will be honest about where a human still has to check, but for sourced answers at scale it holds up well.Can you integrate the OpenAI API with the rest of our tools?
Yes, and it is where we add the most value. We connect the OpenAI API to your apps and orchestrate it through n8n, Make or directly, so drafting, sorting, data 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 on its own. The model does the work where the work happens, instead of your team shuttling text between a chat tab and everything else.ChatGPT or Claude: which should we build on?
It depends on the task, and we are model-agnostic on purpose. ChatGPT and the OpenAI API are strong for broad workflows, Workspace Agents and a huge ecosystem of integrations. For some jobs Claude or an open model fits better, and we say so rather than force one stack. Plenty of teams that get real results end up running a mix. The point is not loyalty to a vendor, it is the right model for each job, which is exactly why we do not wave a partner badge.Do you train our team, and what happens after delivery?
We train the people who will own it, because an agent nobody knows how to use dies right after the demo. That covers how to prompt, what is safe to paste, and when to trust an output versus check it. The build ships with a prompt library, a short playbook and basic AI ops so you can see what is running. After delivery we stay reachable for maintenance and the next round, and everything lives in your own ChatGPT workspace and tools, so pulling it fully in-house later is always an option. Our ChatGPT training goes deeper on the build and safe-rollout side if you want it.
Stop paying for a chat tab nobody uses. Deploy it right.
A free 60-minute audit, your workflows mapped, and a build plan that fits your data and your team, from $2,000 once we know the scope. If you would rather run it in-house afterwards, we hand you the playbook. If we are the right fit, we handle it.