Poozle – Integrate SaaS APIs 10x Faster with GraphQL

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Hey HN, We are Manik, Harshith, and Manoj, the founders of Poozle ( https://www.poozle.dev ). Poozle is a single integration layer that brings together various SAAS APIs. We provide a single GraphQL endpoint for all SAAS APIs, regardless of their protocols. Poozle makes it easy to build integrations for your app into services like GitHub, Jira, Salesforce, Pipedrive, Hubspot, and Gmail. To integrate any API, you typically need to read its documentation, implement its specific authentication, and make very specific calls to its servers. Although this may seem normal, it adds up and becomes time-consuming. The three of us have done numerous integrations into these services for various startups over the years. As a result, we know how painful it can be, particularly when you need to coordinate data from multiple services. Why GraphQL We believe that GraphQL is a query language suitable for all APIs. We can express our data requirements succinctly, even between services, and let a single execution engine determine how to translate those requirements into specific API calls. We have built a GraphQL service that knows how to communicate with each backend API we support, retrieving the exact data you need. Here is the link of out product demo: [ https://www.youtube.com/watch?v=uGIssARKYec&t ] We’d really appreciate your feedback on Poozle. We have a lot we want to improve on, and would love to hear where you want us to go next. Also do support us by starring our repo [ https://github.com/poozlehq/engine ]

Visit product View on Hacker NewsApr 29, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: single, apis · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, io · Missing: https docs, excited, just released

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Incorrect prediction on native model

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