Ai

Airbyte 1.0, Marketplace, AI Assist, GenAI Support and Enterprise GA

Hacker News

Airbyte 1.0, Marketplace, AI Assist, GenAI Support and Enterprise GA

Hi HN friends! We can hardly believe it’s been almost four years since our original HN launch ( https://news.ycombinator.com/item?id=25917403 ). What started as a small project has grown way beyond what we imagined, with over 170,000 deployments and 7,000 companies using Airbyte daily. When we started Airbyte, our mission was simple (though not easy): to solve data movement once and for all. Today feels like a big step toward that goal with the release of Airbyte 1.0 ( https://airbyte.com/v1 ). Reaching this milestone wasn’t a solo effort. It’s taken an incredible amount of work from the whole community and the feedback we’ve received from many of you along the way. We had three goals to reach 1.0: - Broad deployments to cover all major use cases, supported by over 1,200 community contributions. - Reliability and performance improvements (this has been a huge focus for the past year). - Making sure Airbyte fits with your existing production workflow – from Python scripts to Terraform, API, and UI interfaces. It’s been quite the journey, and we’re excited to say we’ve hit those marks! But there’s actually more to Airbyte 1.0! - An AI Assistant to help you build connectors in minutes. Just give it the API docs, and you’re good to go. We’ve also added support for GraphQL APIs to our Connector Builder. - The Connector Marketplace: You can now easily contribute connectors or make changes directly from the no-code/low-code builder. Every connector in the marketplace is editable, and we’ve added usage and confidence scores to help gauge reliability. - Airbyte Self-Managed Enterprise generally available: it comes with everything you get from the open-source version, plus enterprise-level features like premium support with SLA, SSO, RBAC, multiple workspaces, advanced observability, and enterprise connectors for Netsuite, Workday, Oracle, and more. - Airbyte can now power your RAG / GenAI workflows without limitations, through its support of unstructured data sources, vector databases, and new mapping capabilities. It also converts structured and unstructured data into documents for chunking, along with embedding support for Cohere and OpenAI. There’s a lot more coming, and we’d love to hear your thoughts! If you’re curious, check out our launch keynote ( https://airbyte.com/v1 ) and let us know what you think – are there features we could improve? Areas we should explore next? We’re all ears. Thanks for being part of this journey!

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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: new, openai, using · Missing: mac, agents, macos
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua
82%82% 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: way · Missing: mobile apps, ios, personal
64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus, interface, builder · Missing: platform, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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.

Correct prediction on native model

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