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AI integration - ChatGPT App Store

Integrating with the ChatGPT App Store lets your business be invoked directly at the moment of user intent, with AI handling discovery, decision-making, and execution on the user’s behalf.

•Massive Distribution & Visibility

Your app gets exposure to millions of ChatGPT users worldwide. Users can discover your product organically through search, recommendations, categories, and trending lists. You can benefit from impulse adoption without driving all the traffic yourself.

•Brand Credibility & Trust

Being featured in an official store signals legitimacy. Users may trust vetted marketplace listings more than independent sites.

•Easier Customer Onboarding

Users can install and start using your app with minimal friction — no redirection to external auth, downloads, or installs.

What Influences the Cost of a ChatGPT App Store Integration?

What should ChatGPT be able to do for your users?

Should it only provide information, or take actions on the user’s behalf?

  • Will it recommend, compare, book, order, or update accounts?
  • Are actions reversible or business-critical?
  • More automation and responsibility generally mean more design and safety work.
How complex is your business logic?

Are your offerings simple and standardized?

  • Or do pricing, eligibility, or availability depend on multiple rules, regions, or conditions?
  • The more decision logic involved, the more carefully the integration must be designed and tested.
Do users need to log in?

Can the experience work without authentication?

  • Or does it require user accounts, permissions, or role-based access?
  • Authentication and account linking significantly influence integration scope.
How ready are your APIs?

Do you already have stable, well-documented APIs?

  • Or are some steps currently manual or handled internally?
  • Existing, reliable APIs reduce effort and complexity.
How “hands-off” should the experience be?

Should ChatGPT ask for confirmation at every step?

  • Or should it act automatically once intent is clear?
  • Higher levels of automation require stronger safeguards and validation.
Are there regulatory or compliance considerations?

Does your industry require disclaimers, approvals, or strict data handling?

  • Are there actions ChatGPT must never perform?
  • Regulated or sensitive domains require additional design and review effort.
How polished should the user experience be?

Is this an experimental pilot or a flagship customer experience?

  • Does it need branded language, explanations, and tailored flows?
  • More refinement means more design, testing, and iteration.
What happens after launch?

Is this a one-time release?

  • Or do you expect continuous improvements, new capabilities, and scaling?
  • Ongoing evolution often shifts pricing toward phased or retainer models.

FAQ

What does your company actually do in this integration?

We support clients across the entire lifecycle:

  • Identify high-impact ChatGPT use cases
  • Design AI-native, intent-driven user experiences
  • Build and deploy MCP servers and integrations
  • Ensure security, compliance, and App Store review readiness
  • Launch, optimize, and continuously evolve their ChatGPT app

All integrations are designed around your existing environment:

  • Your current APIs
  • Your security and authentication model
  • Your cloud and infrastructure setup
  • Your data ownership and governance requirements

Depending on the level of engagement, we handle:

  • MCP server architecture and implementation
  • Action definitions, schemas, and guardrails
  • API orchestration and workflow logic
  • Authentication and authorization flows
  • Error handling, fallbacks, and edge-case behavior
  • Deployment strategy and hosting guidance

In short, we turn your business into an AI-callable service inside ChatGPT.

Why shouldn’t a business do this alone?

Because ChatGPT integration is not just a technical task. It combines:

  • Conversational UX design
  • AI behavior control
  • Platform-specific constraints
  • Review and compliance requirements
  • Strategic positioning inside an AI ecosystem
How do you help us decide if this is worth doing?

We start with use-case qualification, not implementation. We help answer:

  • Where does ChatGPT meaningfully reduce user friction?
  • Which workflows should (and shouldn’t) be automated?
  • What creates competitive advantage vs. noise?

This avoids building apps that are “technically correct but strategically useless”.

How do you help us stand out from competitors?

We focus on:

  • Intent-first design (what users mean, not what they click)
  • Clear differentiation in metadata and actions
  • High-quality conversational flows
  • Reliability and predictability of outcomes

In the App Store, the best experience wins, not the biggest brand.

How does your service reduce risk?

We reduce risk by:

  • Designing guardrails into AI behavior
  • Preventing over-automation of sensitive actions
  • Ensuring user consent and confirmations
  • Aligning with OpenAI review and policy expectations

This prevents failed submissions, reputational risk, and broken UX.

Why is conversational UX so important?

Because in ChatGPT there is no navigation. The AI is the interface. We design:

  • How the AI asks questions
  • When it acts vs. confirms
  • How it explains results
  • How errors are handled gracefully

Bad UX kills adoption — even if the backend is perfect.

What happens after launch?

Most value comes after launch. We help with:

  • Usage analysis
  • Drop-off identification
  • Prompt and flow optimization
  • Expansion of supported actions
  • Performance and reliability improvements

AI apps are living systems, not one-time builds.

How does this help revenue or growth?

Our clients typically see:

  • Higher intent-to-action conversion
  • Lower user friction
  • Faster decision cycles
  • New acquisition paths
  • Early positioning in AI-driven commerce

This is not just visibility — it’s operational leverage.

Team

Ireneusz Blonar
Ireneusz Blonar
MSc in Software Engineering from Wrocław University of Science and Technology, Poland, and MEng in Industrial Project Management from École des Mines de Saint-Étienne, France.
Aleksandra Koziel
Aleksandra Koziel
MSc in Software Engineering from Silesian University of Science and Technology, Poland. Trained in enterprise-grade system integration and refined through years of hands-on delivery. My experience ranges from global financial institutions such as Goldman Sachs and BGC Partners to building modern, AI-native commerce platforms for smaller, fast-moving businesses.

Contact

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