![]() Open-source features are exactly why Adobe chose to build its new AI assistant that helps users search through Adobe Stock, which has around 100 million images, on Rasa. Rasa’s customers include thousands of developers using its free software, Adobe, Parallon, TalkSpace, Zurich, Allianz, Telekom, and UBS. Rasa’s Open Source Features Drive its Use This makes using Rasa much more appealing to companies who don’t want to work with organizations who might be competitors. Regardless of the plan used, all of Rasa’s tools run on a company’s own training data, and the company is able to decide where they want to host their bots. Rasa has created several open-source tools that can be used for free and also has a paid enterprise version with extra features, like more tools, customer support, testing and training tools, and production container deployment. Companies of all kinds use the model with unstructured information to train their bots. In practice, Rasa’s approach to addressing a machine learning problem manifests itself in building an open-source model that is developer friendly. What we do is more is address this as a mathematical, machine learning problem rather than one of language. Rasa then became a company focusing on fixing shortcomings of chatbots. The company is known for its open-source platform for third parties that allows users to design and manage their own conversational chatbots, using both text and voice.Īlexa Weidauer and Alan Nichols co-founded Rasa 2.5 years ago “when chatbot hype was at its peak.” Weidauer told TechCrunch that their original path to build chatbots stopped when they realized developer tools to make chatbots were not there. Rasa announced today it has raised $13 million in a Series A round of funding led by Accel, with participation from Basis Set Ventures, Open AI’s Greg Brockman, UiPath’s Daniel Dines, and Hashicorp’s Mitchell Hashimoto.
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