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

Hacker News

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://news.ycombinator.com/item?id=27446200 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://github.com/airyhq/airy And we are of course happy to answer your questions!

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apps, new · Missing: mac, agents, macos
89%89% 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 · Strong signals: including · Missing: supports, reddit linkedin, podcasting
83%83% 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
81%81% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal, apps · Missing: mobile apps, ios, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
34%34% 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 · Strong signals: smart · 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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