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Uniphore, the global technology company known for its conversational AI and automation solutions, is taking a step towards simplifying how enterprises develop retrieval augmented generation (RAG) applications. The company today announced the launch of X-Stream, a new layer in its core data and AI platform that enables knowledge-as-a-service and brings together powerful tools, connectors and controls for enterprises to mobilize their multimodal datasets for grounded, domain-specific AI applications.
At its core, what X-Stream gives enterprises is a unified and open architecture to combine all the fragmented steps of preparing AI-ready data into a seamless process — essentially serving as a one-stop solution and eliminating the need to use multiple tools across the stack.
“With X-Stream, customers can fine-tune their data, convert it into AI-ready knowledge and seamlessly feed it into Uniphore’s industry-specific, production-ready small language models or build their own. Our data scientists and engineers, drawing on years of experience, have solved for accuracy and hallucinations, ensuring safety and guiding customers towards AI sovereignty,” Umesh Sachdev, the CEO of the company, told VentureBeat.
Solving the data problem for RAG
With the rise of generative AI, the idea of RAG, where AI uses information from a specified set of databases and sources to provide accurate answers to complex questions, has become quite prevalent. Most enterprises today are racing to build dedicated RAG-based search and chat apps that could use their internal knowledge base to provide hallucination-free responses and ultimately drive efficiencies across different functions.
However, when it comes to building (and scaling) such apps, things tend to get a little tricky — especially on the data front.
In almost every case of RAG, the information that an organization wants to use is spread across different sources and formats, from structured tables to unstructu …