Case / B2C product · Prostir Build
Prostir Build turns expertise into a product customers can use.
Prostir Build is Managed Code's own customer-facing AI product. It turns what a creator or a team knows into an AI agent people can open in ChatGPT, Claude, a website, or a web dashboard.
Product case. What follows is about which fit is right; it does not claim that every company needs the same setup or the same delivery path.
- Works in
- ChatGPT
- Claude
- Gemini
- Coding agents
Direct answer
Use Prostir Build when the job is to package expertise for customers or a wide audience. Build a dedicated internal workflow when the job runs inside one company, with company sign-in, private systems, and that company's own rules
The B2C job01
Package what you know for people outside your company.
Prostir's public product story is aimed at people with expertise who want it to run as an AI agent, without building everything around it from scratch. The site describes agents that use files, rules, a shareable link, customer accounts, payments, usage limits, and a dashboard.
That is a problem about serving customers. The agent has to be useful, easy to find, and easy to run for a creator, a consultant, a course business, or a team serving an audience.
Prostir Build · aboutProstir's site describes
Files
Rules
A shareable link
Customer accounts
Payments
Usage limits
A dashboard
Without building everything around it from scratch.
Distribution02
Put the agent where the customer already is.
The public Prostir site describes one agent link that opens inside ChatGPT, Claude, or a website. The choice that matters is not which model you use. It is where the customer can find the agent, sign in, and come back to it.
For a product sold to customers, the owner also needs a simple way to see who used the agent and which access or payment terms apply.
Prostir Build · product overviewProstir's site · one agent link
ChatGPT
Claude
A website
Where the customer can find it, sign in, and come back.
Enterprise differs03
An internal workflow starts where the company draws its lines.
An internal build is not a bigger version of a customer-facing agent. It usually starts with employee sign-in, approved systems, access that follows the person's role, a record you can audit, and one narrow task inside a process the company already runs.
The business may need the agent to use private knowledge or do things in internal systems. That calls for your product deciding who is allowed to do what, each action written down exactly, a point where someone confirms, and someone reviewing how it runs. A general public link is not that.
An internal workflow begins with
Employee sign-in
Approved systems
Access that follows the role
A record you can audit
One narrow task inside an existing process
Your product decides who may do what, not a public link.
Pick the right first question04
Ask who the user is, and where the record has to live.
If the answer is “a customer pays to use what I know,” the B2C product model is a strong place to start. If the answer is “a signed-in employee must finish a task the company controls,” the enterprise pattern fits better.
The technology can look the same. The promise you are making is not.
Ask who the user is
“A customer pays to use what I know.”
B2C product“A signed-in employee must finish a task the company controls.”
Enterprise patternThe technology can look the same. The promise is not.
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.