Noodle Seed – Create ChatGPT Apps for businesses to reach 800M users

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Hi HN! I’m Uzair, Founding Engineer of Noodle Seed. We enable businesses to deploy native apps inside ChatGPT conversations when users need recommendations. What we built: A multi-tenant no-code platform that helps businesses create custom ChatGPT Apps. When someone asks “find me a legal firm in Austin,” businesses using our platform appear with their own branded app - complete with UI components, interactive elements, and real-time information. Not random results from old training data, but actual custom experiences with each business’s branding. Try it: We’re in limited beta with founding members. You can create and test an app yourself in ChatGPT’s Developer Mode - takes just a few minutes (email me for examples - don’t want to spam here). Technical details: We generate MCP servers that expose business services as tool contracts. When ChatGPT’s function-calling matches user intent, we return real-time data through OAuth-authenticated sessions (for now we’re not releasing OAuth to our users so they can test with less friction). What was hard: Building a no-code abstraction layer over MCP servers, OAuth flows, and JSON schemas while maintaining flexibility for custom experiences. Every business wants different functionality - appointment booking, product catalogs, lead forms - but ChatGPT’s Apps SDK has strict requirements. We had to create a system that generates compliant tool contracts and web components automatically while still allowing businesses to customize their UI and branding. What surprised me: Most businesses / startups have no idea ChatGPT Apps even exist. The October 6 launch flew completely under the radar outside tech circles. What I’m unsure about: Are we too early? Will businesses pay for AI discovery before it’s proven? We’re onboarding founding members now - businesses / startups that want to establish AI discovery presence before their competitors. If you run a company or know someone who should be discoverable when people ask AI for recommendations, join our waitlist at [noodleseed.com]. Would love feedback on the approach and whether anyone else is tackling AI discovery differently.

Visit product View on Hacker NewsOct 28, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: mcp, apps, user · Missing: mac, agents, macos

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: apps, users · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: training, active · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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