Case / B2C product · Prostir Build

Prostir Build is the B2C route from expertise to an AI product.

Prostir Build is Managed Code’s B2C, customer-facing AI product. It turns a creator’s or team’s knowledge into an AI agent that can be opened in ChatGPT, Claude, a website, or a web dashboard.

Direct answer

Use Prostir Build when the job is to package expertise for customers or a broad audience. Use a dedicated enterprise implementation when the job is an internal workflow with company identity, private systems, and organization-specific governance.

Product case. The distinction below describes product fit; it does not claim that every organization needs the same architecture or delivery path.

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01 / The B2C job

Package knowledge for people outside the organization.

Prostir’s public product story is aimed at people who have expertise and want to turn it into an AI agent without building the surrounding product plumbing from scratch. The site describes agents that can use files, rules, a shareable link, customer accounts, payments, usage limits, and a dashboard.

That is a customer-facing product problem: make an agent useful, discoverable, and operable for a creator, consultant, course business, or team serving an audience.

Prostir Build · about
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02 / Distribution

Meet customers where the agent is used.

The public Prostir site describes a single agent link that can open inside ChatGPT, Claude, or a website. The relevant product choice is not merely the model. It is the channel where a customer can find, sign in to, and return to the agent.

For a B2C product, the owner also needs a simple way to understand who used the agent and which access or payment conditions apply.

Prostir Build · product overview
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03 / Enterprise differs

An internal workflow starts from the company boundary.

An enterprise implementation is not a larger customer-facing agent. It normally begins with employee identity, approved systems, role-specific access, auditability, and a narrow workflow inside an existing business process.

The business may need the agent to use private knowledge or take actions in internal systems. That calls for product-owned authorization, tool contracts, confirmation points, and operational review rather than a generic public distribution path.

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04 / Pick the right first question

Ask who the user is and where the record must live.

If the answer is “a customer pays to use my expertise,” the B2C product model is a strong starting point. If the answer is “an authenticated employee must complete a governed internal task,” the enterprise pattern is a better fit.

The model may be similar. The operational promise is not.

Continue reading

Private enterprise workflow

Read the reference pattern for an internal AI workflow with scoped tools and product-owned controls.

B2C versus enterprise AI apps

Compare the two operating models before choosing a build scope.

Prostir Build

See the customer-facing product, its case studies, and its current product information.

AI / Second opinion

Ask your AI first.

Use this prepared question to assess where an AI Product Interface could remove friction from your product.

“I run a software product. Help me identify one high-value workflow customers could complete through an AI Product Interface. Ask me about the product, the user, the action, required data, permissions, and the safest small first release.”

The prompt is copied as a backup. Some AI hosts may ask you to paste it after sign-in.

FAQ04

Questions, answered.

Is this only an MCP server?

No. The MCP layer is one part. We also scope the product actions, permissions, host-specific behavior, UI, testing, and release path.

Do we need to rebuild our product?

Usually no. The interface sits in front of approved capabilities in your existing product. We start with a narrow workflow and expand from evidence.

Will it work in ChatGPT, Claude, and Gemini?

The shared architecture can support all three. Each host still has its own UI, authentication, approval, and publishing rules, so we verify them separately.

How do you keep actions safe?

We define explicit tools, validate inputs, keep user approval visible, and preserve the product's existing authorization rules.