Retrieval-augmented generation (RAG) is becoming more of a focus in company discussions as businesses look to increase the accuracy of GenAI, according to findings from research and analysis company GlobalData’s Company Filings Analytics Database.
False responses know as ‘hallucinations’ generated by AI models are one of the last barriers to human-grade responses from GenAI tools. RAG is a solution to this problem and companies are using it to extend their focus to real-time external data to contextualise and refine the accuracy of generated responses.
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Misa Singh, business fundamentals analyst at GlobalData, said: “While many companies are still concentrating on GenAI, others have already started seeing RAG as an opportunity. The discussions mainly revolved around driving better results, minimising AI hallucinations and providing technical support to products. Companies are also collaborating to integrate their offerings to build RAG pipelines and answer questions more promptly.”
Indeed, Amazon built Amazon Bedrock, which along with the broadest selection of LLMs also has RAG to expand model’s knowledge base. This allows to safeguard what questions applications will answer and agents to complete multistep tasks.
Examples of increased RAG focus among companies identified by GlobalData include Progress Software’s new Progress Data Platform, which is the integration of MarkLogic and Progress Technologies features both semantic and vector capabilities to power RAG in AI application. The platform provides contextual links to corporate information and knowledge within the responses. Users can see where the answers came from, what they mean, and how they are relevant to the business. This drives dramatically better results of GenAI powered responses and minimises AI hallucinations.
Another example is Innovation Technology Group which is focusing on introducing and polishing the RAG and Agent engineering frameworks to provide strong technical support for the iterative upgrades of ChatDoc, ChatRobot Pro and other products. Pure Storage Inc revealed in its earnings call that it sees RAG as an opportunity.
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By GlobalDataConfluent has partnered with Pinecone for its vector database architecture “Pinecore serverless.” This integration allows customers to build RAG pipelines that will allow customers to bring together the real-time state of their proprietary data sources with general purpose AI models.
