Discover how companies are responsibly integrating AI in production. This invite-only event in SF will explore the intersection of technology and business. Find out how you can attend here.
Today’s large language models (LLMs) are increasingly complex, but often, the data they use to generate responses doesn’t extend beyond their training — meaning it can often be weeks or even months out of date.
This has made retrieval-augmented generation (RAG) essential for modern enterprise, as it enables up-to-date, company-specific outputs. Still, retrieval presents its own issues when it comes to accuracy, scalability and security; enterprise content is intricate and complex.
RAG platform Pryon says it has overcome many of these challenges, and is today extending its capabilities with the Pryon Retrieval Engine. The platform securely extracts information from complex, sprawled content to help organizations get the most out of today’s sophisticated AI tools.
“The reliability of generated content is not there, bias in the results is a big problem,” Chris Mahl, Pryon’s president, COO and board member,” told VentureBeat. “Information in some of these models is frozen in time. So, while I may be asking a question that we think is really smart, the answer is grounded in history, not in current events. Which is a big problem.”
VB Event
The AI Impact Tour – San Francisco
Join us as we navigate the complexities of responsibly integrating AI in business at the next stop of VB’s AI Impact Tour in San Francisco. Don’t miss out on the chance to gain insights from industry experts, network with like-minded innovators, and explore the future of GenAI with customer experiences and optimize business processes.
Request an invite
Pulling together a ‘collection’ of company-specific data
Current methods of ingestion often struggle to handle complex document-based content, and accuracy is difficult at scale, M …
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Discover how companies are responsibly integrating AI in production. This invite-only event in SF will explore the intersection of technology and business. Find out how you can attend here.
Today’s large language models (LLMs) are increasingly complex, but often, the data they use to generate responses doesn’t extend beyond their training — meaning it can often be weeks or even months out of date.
This has made retrieval-augmented generation (RAG) essential for modern enterprise, as it enables up-to-date, company-specific outputs. Still, retrieval presents its own issues when it comes to accuracy, scalability and security; enterprise content is intricate and complex.
RAG platform Pryon says it has overcome many of these challenges, and is today extending its capabilities with the Pryon Retrieval Engine. The platform securely extracts information from complex, sprawled content to help organizations get the most out of today’s sophisticated AI tools.
“The reliability of generated content is not there, bias in the results is a big problem,” Chris Mahl, Pryon’s president, COO and board member,” told VentureBeat. “Information in some of these models is frozen in time. So, while I may be asking a question that we think is really smart, the answer is grounded in history, not in current events. Which is a big problem.”
VB Event
The AI Impact Tour – San Francisco
Join us as we navigate the complexities of responsibly integrating AI in business at the next stop of VB’s AI Impact Tour in San Francisco. Don’t miss out on the chance to gain insights from industry experts, network with like-minded innovators, and explore the future of GenAI with customer experiences and optimize business processes.
Request an invite
Pulling together a ‘collection’ of company-specific data
Current methods of ingestion often struggle to handle complex document-based content, and accuracy is difficult at scale, M …nnDiscussion:nn” ai_name=”RocketNews AI: ” start_sentence=”Can I tell you more about this article?” text_input_placeholder=”Type ‘Yes'”]