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Show HN: Airy – Open-Source Platform for Real-Time ML/AI and Data Streaming

15 点作者 skandergarroum超过 2 年前
Why Airy?<p>- Easily deploy mature streaming infrastructure powered by Apache Kafka with our open-source streaming app framework.<p>- Build real-time data pipelines and make real-time data universally accessible.<p>- Join historical and real-time data in the stream to create smarter ML and AI applications.<p>- For data and dev ops teams: Standardize complex data ingestion and stream data directly to standard and customized applications, using pre-built, easily configured connectors.<p>- For engineering teams: Significantly simplify deployment and reduce development times and increase the robustness of your infrastructure and apps.<p>-----------------<p>About Airy<p>Mid last year we launched our open-source conversational platform enabling developers to ingest and process conversational and customer data in real-time: <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=27446200" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=27446200</a><p>Airy has now evolved with its use cases into an open-source streaming app framework to train context-aware ML models and supply them with both historical and real-time data.<p>By ingesting all real-time events and continuously processing, aggregating and joining them in the stream, development time can be significantly reduced. Through integrations with pre-built and easily configured connectors, events are consumed from any source, including business systems such as ERP&#x2F;CRM, conversational sources, third party APIs. Airy also comes with an SDK to build custom connectors to any source.<p>-----------------<p>Our vision<p>We believe continuously improved AI and ML will increasingly be at the core of enterprise decision-making and customer-facing technologies.<p>Adopting Airy’s open-source streaming app framework provides enterprise teams with a highly scalable and standardized platform to install, run and monitor streaming components and connectors.<p>This delivers better results through automation &amp; personalization, while significantly reducing time to production for engineering teams.<p>You can start trying it out by visiting our website: <a href="https:&#x2F;&#x2F;airy.co" rel="nofollow">https:&#x2F;&#x2F;airy.co</a> If you like what we are doing, please give us a star on Github: <a href="https:&#x2F;&#x2F;github.com&#x2F;airyhq&#x2F;airy" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;airyhq&#x2F;airy</a><p>And we are of course happy to answer your questions!

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