Show HN: Airy – Open-Source Platform for Real-Time ML/AI and Data Streaming https://ift.tt/Zj15wKm

Show HN: Airy – Open-Source Platform for Real-Time ML/AI and Data Streaming Why Airy? - Easily deploy mature streaming infrastructure powered by Apache Kafka with our open-source streaming app framework. - Build real-time data pipelines and make real-time data universally accessible. - Join historical and real-time data in the stream to create smarter ML and AI applications. - 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. - For engineering teams: Significantly simplify deployment and reduce development times and increase the robustness of your infrastructure and apps. ----------------- About Airy Mid last year we launched our open-source conversational platform enabling developers to ingest and process conversational and customer data in real-time: https://ift.tt/MZU7opm 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. 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/CRM, conversational sources, third party APIs. Airy also comes with an SDK to build custom connectors to any source. ----------------- Our vision We believe continuously improved AI and ML will increasingly be at the core of enterprise decision-making and customer-facing technologies. 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. This delivers better results through automation & personalization, while significantly reducing time to production for engineering teams. You can start trying it out by visiting our website: https://airy.co If you like what we are doing, please give us a star on Github: https://ift.tt/xTFf7dH And we are of course happy to answer your questions! https://airy.co November 29, 2022 at 11:41PM

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