Rasa X – Algorithms alone won't solve conversational AI
We're excited to announce Rasa X, our new product for developers in early access. Also, our open source framework Rasa is now available in 1.0
Rasa X – Algorithms alone won't solve conversational AI launched on May 21, 2019 with 18 votes, #883 of 3,072 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 7 years on.
In plain words
Rasa X is a platform for building and improving conversational AI systems. It provides tools for developers to create, test, and refine chatbots and voice assistants. The platform focuses on helping teams move beyond basic algorithmic approaches to develop more sophisticated conversational experiences. Rasa X is designed for organizations looking to deploy production-ready dialogue systems with capabilities for continuous learning and improvement from real conversations.
written from the facts on this page · September 2026
From the sources
Update: A lot of things have changed since this post was written. Rasa X, the freemium companion tool to Rasa Open Source, is no longer supported or maintained, and we are currently focused on the development of the Rasa Enterprise platform. To learn more about this, you can check out this blog post At Rasa, we're building the standard infrastructure for conversational AI so that all developers can create the best text- and voice-based assistants. In 2016 we wrote that we don't know how to build conversational software yet . Since then, we've been doing research and shipping code, tackling the machine learning side of the problem. Rasa NLU and Core were our first major moves towards better…from blog.rasa.com
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An open source framework for voice assistants2024 · github.com · ▲346I've been obsessed for the past ~year with the possibilities of talking to LLMs. I built a bunch of one-off prototypes, shared code on X, started a Meetup group in SF, and co-hosted a big hackathon. It turns out that there are a few low-level problems that everybody building conversational/real-time AI needs to solve on the way to building/shipping something that works well: low-latency media transport, echo cancellation, voice activity detection, phrase endpointing, pipelining data between models/services, handling voice interruptions, swapping out different…


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