In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation.
In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI.
If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways:
Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter.
As Joe aptly put it, “Risk increases as access to knowledge assets decreases ... Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”
The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.
As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”
Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers.
As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”
Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.
Ready to dive deeper? Reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world's first enterprise-grade Knowledge AI Platform.
In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation.
In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI.
If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways:
Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter.
As Joe aptly put it, “Risk increases as access to knowledge assets decreases ... Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”
The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.
As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”
Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers.
As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”
Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.
Ready to dive deeper? Reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world's first enterprise-grade Knowledge AI Platform.
In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation.
In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI.
If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways:
Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter.
As Joe aptly put it, “Risk increases as access to knowledge assets decreases ... Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”
The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.
As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”
Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers.
As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”
Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.
Ready to dive deeper? Reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world's first enterprise-grade Knowledge AI Platform.
Why knowledge friction costs enterprises thousands of hours of productivity. Four common approaches to solving the enterprise productivity problem — and why they fall shortHow to unlock the value of AI and solve your productivity problem with a Knowledge AI platform
70% of employees report spending an hour or more searching for a single piece of information.*
Companies are creating more content and data than ever – but most of it isn’t discoverable. This frustrating disconnect between content creators and content consumers is what we call knowledge friction. And it costs enterprises thousands of hours of productivity.
*2024 Survey on Information Discovery, Unisphere Research.
Companies have tried various solutions to generate actionable answers from their existing content, yet the enterprise productivity problem remains. Where web search, legacy enterprise search, homegrown solutions, and AI startups all fall short, Knowledge AI is eliminating knowledge friction once and for all.
Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), an enterprise Knowledge AI platform swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers for your teams.
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Stop endlessly searching through PubMed to find the right citation, research guidance, or trial data. RAE lets you ask a question, queries millions of information sources, and delivers the right answer in less than a second, pointing you to the source document(s) in case you’d like to gather more context.
Your own research data may contain insights that are even more valuable than the information hidden in MEDLINE and other biomedical literature. That’s why RAE allows researchers to upload their own research, such as clinical trial findings, patient data, and internal unpublished research papers.
RAE delivers trustworthy, verifiable, always up-to-date answers, which are critical in a research setting. RAE’s best-in-class retrieval model uses advanced machine learning, computer vision, and optical character recognition to read complex information — even handwritten documents and diagrams — like a human would. RAE never hallucinates, since it only pulls from trusted research content, and delivers over 90% accuracy out of the box (with further improvements over time).
For many organizations, life sciences research can comprise tens of thousands of voluminous research articles. RAE’s massive storage and compute resources enable it to ingest terabytes of research data — including PDFs, text files, images, video, and more — and transform that data into accurate answers.
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To ensure private research data and queries remain private, RAE runs entirely on-premises, not in a public cloud environment. RAE comes preloaded with Pryon, a Knowledge AI platform. Pryon’s AI models do not train on your data, so your data remains yours and yours alone. The system additionally ensures security against external parties with a self-contained, SOC 2 Type II-compliant architecture. All running securely on-prem on Dell PowerEdge servers.
“We can’t wait to see how pharmaceutical companies, research institutes, and development organizations use the Pryon | Dell Research Answer Engine. With this solution, life science experts can spend less time searching PubMed and internal resources for answers and more time conducting game-changing research.”
— Alex Long, Head of Strategy, Life Sciences at Dell Technologies
RAE helps accelerate the research process by enabling researchers to quickly get answers to their questions directly from trusted sources, such as MEDLINE and private research. Life science researchers no longer need to waste time and energy hunting for valuable information when they could instead be helping develop new treatments.
- Where stalled information access is holding enterprises back
- The leading barriers to delivering business-critical information to end users
- The top AI use cases enterprise leaders are exploring for 2024
- Strategies for implementing AI solutions without exposing your organization to risk
92% of enterprise leaders agree that access to fast, accurate information from unstructured content is vital to their business.
70% of leaders report that employees in their organization spend more than an hour looking for a piece of information, with nearly a quarter (23%) spending more than 5 hours.
The two leading use cases for AI involve helping users better understand and get answers from information spread across the enterprise.
In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation.
In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI.
If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways:
Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter.
As Joe aptly put it, “Risk increases as access to knowledge assets decreases ... Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”
The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.
As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”
Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers.
As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”
Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.
Ready to dive deeper? Reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world's first enterprise-grade Knowledge AI Platform.
In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation.
In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI.
If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways:
Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter.
As Joe aptly put it, “Risk increases as access to knowledge assets decreases ... Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”
The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.
As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”
Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers.
As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”
Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.
Ready to dive deeper? Reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world's first enterprise-grade Knowledge AI Platform.
Read this guide to:
Government agencies need to ensure employees, service members, and citizens quickly and easily receive the answers they need to drive productivity and enable decision advantage.
Internal content authors work diligently to produce and update content, including policies, procedures, and lessons learned. Yet staff, managers, and senior leaders still lose valuable time wading through pools of siloed information to find answers. As a result, the gap between critical information and those who need it most continues to widen.
Government agencies need to ensure employees, service members, and citizens quickly and easily receive the answers they need to drive productivity and enable decision advantage.
With the right GenAI solutions in place, staff and service members can take on challenges with greater speed and intelligence.
Not every GenAI solution on the market is fit to meet the specific needs of government agencies. Implementing GenAI in a regulated environment requires careful consideration of four critical factors to ensure success:
Many federal agencies are turning to Retrieval-Augmented Generation (RAG) to support their GenAI solutions. RAG is a framework that combines retrieval and generative capabilities to deliver accurate and trustworthy responses.
This approach mitigates common issues with GenAI tools, such as hallucinations and ensures that responses are based on authoritative content with clear source attribution.
