Example / Customer follow-up
Customer follow-up in ChatGPT starts with one approved change.
A good first workflow does not replace your CRM. It closes the small gap between a clear request and the approved update that already belongs in your product.
Reference workflow. It shows a pattern we build, not a customer result or a live client integration.
- Works in
- ChatGPT
- Claude
- Gemini
- Coding agents
Direct answer
For a customer follow-up, let the chat find one account, show only what matters, suggest the next step, and require a clear confirmation before your product changes anything
The job01
Name the thing that counts as done.
“Follow up with this customer” is too vague to hand over as one command. Your product team decides what the finish line is: a saved CRM note, a booked meeting, a drafted message, or a task for an account owner.
That one sentence gives the workflow an edge. It also means you can tell a person exactly what changed once the conversation ends.
Before anything changes
Find the right account from a reliable ID.
ReadRead a small slice of recent activity and who owns the account.
ReadSuggest one next step before anything changes.
PrepareThen, and only then, a confirmed change.
What the AI can touch02
Keep the list of actions short and named.
The AI does not need every part of your CRM. A first version may need only three actions: read, draft, and one change the customer confirms. Each action spells out what it needs, what it gives back, and which of your product's rules can turn it down. The layer offers those actions and nothing else.
That is easier to test than an assistant told to “handle follow-ups” through an open-ended connection to your API.
Model Context Protocol · tools specificationThe layer · what this workflow can use
app.read_record
Readapp.draft_update
Draftapp.update_record
Confirmed changeEvery other part of your product stays out of reach.
Confirmation03
Show the change before it happens.
The chat can lay out the account, the date, the owner, and the message before it asks the person to continue. Your product then applies the same permission and validation checks it would apply outside the chat.
The confirmation step is not decoration. It gives the person a chance to catch the wrong customer, a missing detail, or an action that should stay with an account owner.
app.update_recordRecord#1042
OwnerDana R.
ProposedLog the follow-up note · status “In progress”
Result04
Hand back something a person can check.
A good answer says what changed, what got booked, and what still needs attention. It links back to the source record when that helps, instead of leaving the person with a chat message they cannot trace.
Your CRM stays the record of the work. ChatGPT is where the request arrives, not a second version of the truth.
Done across your product
Record updated · #1042
Calendar booked · Thu 10:00
Your permissions and your record of what happened stay in charge.
AI / Second opinion05
Not sure where to start? Ask an AI.
Paste this question into ChatGPT, Claude, or Gemini. It walks you through finding the one task your customers would most want to finish by chatting, instead of clicking through your app.
“I run a software product. Help me identify one high-value workflow my customers could finish inside ChatGPT instead of switching between tabs. Ask me about the product, the user, the action, the data it needs, permissions, and the safest small first release.”
The prompt is copied as a backup. Some AI chats may ask you to paste it after sign-in.
FAQ06
Questions, answered.
Is this just an MCP server?
No. The server is one piece. We do the whole job: we pick the customer task, set who can do what, handle the quirks of each AI chat, make the actions run fast, add monitoring, test it, and ship it.
Do we have to rebuild our product?
Almost never. Our layer sits in front of what your product already does. We start with one small workflow and grow from what works.
Will it work in ChatGPT, Claude, and Gemini?
The same build can serve all three. Each one has its own sign-in, look, approval step, and publishing rules, so we set up and test each one separately.
How do you keep it safe?
Your product decides what is allowed, and we keep that in charge. Every action is spelled out, every input is checked, and the customer sees an approval step before anything happens. Our layer sits beside your product, not inside it.
Where does it run? Does it touch our code?
It runs as a separate service in front of your product. It never goes into your code, and you still own your data.
What does it cost, and how fast?
A first workflow starts at €3,200 and goes live in about 7 days.
Contact us07
Now build yours
Send us your product, who uses it, and the action you have in mind. We will tell you the smallest version worth building, and whether it is a €3,200 first workflow or something that needs a closer look first.