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Karrio – Open-Source Multi-Carrier Shipping API

Hacker News

Karrio – Open-Source Multi-Carrier Shipping API

Hey HN! Daniel and Delali here; we are working on Karrio, an open-source shipping infrastructure. Our focus is on making it easy to integrate shipping into platforms. With Karrio’s open-source and universal shipping API, you can set up connections to a worldwide network of shipping carriers for national, international and last-mile services but also build your own network of local carriers. You can seamlessly add built-in shipping functionalities to your platform, enabling users to fetch live rates, buy labels, track packages, and more. You can check out our Github repo here: https://github.com/karrioapi/karrio . For developers in the logistics space, carrier integration is often a painful experience. We believe that an open-source solution is a viable alternative to building a shipping system from scratch in-house or getting locked in with a Saas multi-carrier API. Karrio aims to put you in control of your shipping network with lower engineering costs. (see how to get started here: https://docs.karrio.io/quick-start ). So far, we’ve built a unified shipping API compatible with most major carriers, such as FedEx, UPS, DHL, USPS, Canada Post, and more. With the flexibility of open-source, Karrio has interoperability with other multi-carriers and 3PL (EasyPost, Freightcom, etc.). And we plan on building more integrations. Karrio is evolving with the help of our community of early adopters, and we want to keep that going. Checkout our README to get involved with the project, file issues and request or contribute carrier integrations We currently offer a managed cloud service in private beta, with a pay-as-you-go plan for platforms and custom prices for enterprise customers. Don’t hesitate to reach out if you have any questions. We would love to hear your feedback and how Karrio can help with your project.

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, open · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, compatible · Missing: supports, reddit linkedin, podcasting
84%84% 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, io · Missing: https docs, excited, just released
80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr, saas · Missing: mrr, revenue, profit
16%16% 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.

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