We’ve all felt the pain of needing a quick answer at work and spending hours checking different systems to find it — searching around for the right file, attempting to remember the right keywords to use, trying to get time with an already overburdened SME, and feeling frustrated by a lack of results. Then, once you think you’ve found the content you need, you spend more time reading through it, parsing the information to pinpoint the answer to your question. All the while crossing your fingers that the file is up-to-date and the information inside is verified.
Sound familiar?
You’re not alone. Pryon recently worked with Unisphere Research to survey a cross-industry group of enterprise leaders and knowledge workers on this problem. The survey found that employees waste hours weekly searching for information scattered across the enterprise. Yet, much of an organization’s content still goes unused. More than one out of five respondents estimate that less than half of the unstructured information in their organization is readily available. And only a handful (6%) reported the complete availability of their organization’s information.
1 in 5 enterprise leaders report that less than half of their organization’s content is readily available.
Knowledge friction is the disconnect between enterprise authors and key content consumers. It is a constant consequence to productivity, operations, compliance, and revenue. Content authors — such as marketing, support managers, sales enablement, and product teams — invest high-quality time and effort producing informative content for end users — from salespeople and researchers to operations and customer support teams. Even after all this, end users still struggle to find and access the answers they need.
While organizations invest billions of dollars every year in content management software and enterprise search systems to try and solve their knowledge friction problems, they've seen little to no results. In fact, introducing too many of these systems compounds knowledge friction. The 2024 Survey on Enterprise Information Discovery found that having multiple systems to search across is the leading obstacle to delivering necessary and timely information to employees, customers, and partners.
.webp)
Difficulties in searching across systems (56%) was followed closely by problems with information and data silos (55%) and issues with information and data quality (52%) as the leading causes of knowledge friction. Other top obstacles include challenges in finding the correct search terms to locate desired information (46%) and insufficient content sharing (44%).
Knowledge friction can look different and have varying impacts depending on your industry and function. Here are some examples of warning signs to watch out for by department and the negative business outcomes that come with them:
Anyone can increase these truths from their point of need. And these symptoms and impacts are just the tip of the iceberg. The report from Unisphere Research identified 21 risks of stalled access to business-critical information:
Since legacy content management systems and enterprise search engines have fallen short, many enterprises are looking to Knowledge AI to tackle knowledge friction. Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), Knowledge AI swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers. This means no more endless searching through complex systems or wasting time on outdated information. Instead, teams can rely on a Knowledge AI platform for instant access to reliable answers, precisely when they need them.
We’ve all felt the pain of needing a quick answer at work and spending hours checking different systems to find it — searching around for the right file, attempting to remember the right keywords to use, trying to get time with an already overburdened SME, and feeling frustrated by a lack of results. Then, once you think you’ve found the content you need, you spend more time reading through it, parsing the information to pinpoint the answer to your question. All the while crossing your fingers that the file is up-to-date and the information inside is verified.
Sound familiar?
You’re not alone. Pryon recently worked with Unisphere Research to survey a cross-industry group of enterprise leaders and knowledge workers on this problem. The survey found that employees waste hours weekly searching for information scattered across the enterprise. Yet, much of an organization’s content still goes unused. More than one out of five respondents estimate that less than half of the unstructured information in their organization is readily available. And only a handful (6%) reported the complete availability of their organization’s information.
1 in 5 enterprise leaders report that less than half of their organization’s content is readily available.
Knowledge friction is the disconnect between enterprise authors and key content consumers. It is a constant consequence to productivity, operations, compliance, and revenue. Content authors — such as marketing, support managers, sales enablement, and product teams — invest high-quality time and effort producing informative content for end users — from salespeople and researchers to operations and customer support teams. Even after all this, end users still struggle to find and access the answers they need.
While organizations invest billions of dollars every year in content management software and enterprise search systems to try and solve their knowledge friction problems, they've seen little to no results. In fact, introducing too many of these systems compounds knowledge friction. The 2024 Survey on Enterprise Information Discovery found that having multiple systems to search across is the leading obstacle to delivering necessary and timely information to employees, customers, and partners.
Difficulties in searching across systems (56%) was followed closely by problems with information and data silos (55%) and issues with information and data quality (52%) as the leading causes of knowledge friction. Other top obstacles include challenges in finding the correct search terms to locate desired information (46%) and insufficient content sharing (44%).
Knowledge friction can look different and have varying impacts depending on your industry and function. Here are some examples of warning signs to watch out for by department and the negative business outcomes that come with them:
Anyone can increase these truths from their point of need. And these symptoms and impacts are just the tip of the iceberg. The report from Unisphere Research identified 21 risks of stalled access to business-critical information:
Since legacy content management systems and enterprise search engines have fallen short, many enterprises are looking to Knowledge AI to tackle knowledge friction. Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), Knowledge AI swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers. This means no more endless searching through complex systems or wasting time on outdated information. Instead, teams can rely on a Knowledge AI platform for instant access to reliable answers, precisely when they need them.
We’ve all felt the pain of needing a quick answer at work and spending hours checking different systems to find it — searching around for the right file, attempting to remember the right keywords to use, trying to get time with an already overburdened SME, and feeling frustrated by a lack of results. Then, once you think you’ve found the content you need, you spend more time reading through it, parsing the information to pinpoint the answer to your question. All the while crossing your fingers that the file is up-to-date and the information inside is verified.
Sound familiar?
You’re not alone. Pryon recently worked with Unisphere Research to survey a cross-industry group of enterprise leaders and knowledge workers on this problem. The survey found that employees waste hours weekly searching for information scattered across the enterprise. Yet, much of an organization’s content still goes unused. More than one out of five respondents estimate that less than half of the unstructured information in their organization is readily available. And only a handful (6%) reported the complete availability of their organization’s information.
1 in 5 enterprise leaders report that less than half of their organization’s content is readily available.
Knowledge friction is the disconnect between enterprise authors and key content consumers. It is a constant consequence to productivity, operations, compliance, and revenue. Content authors — such as marketing, support managers, sales enablement, and product teams — invest high-quality time and effort producing informative content for end users — from salespeople and researchers to operations and customer support teams. Even after all this, end users still struggle to find and access the answers they need.
While organizations invest billions of dollars every year in content management software and enterprise search systems to try and solve their knowledge friction problems, they've seen little to no results. In fact, introducing too many of these systems compounds knowledge friction. The 2024 Survey on Enterprise Information Discovery found that having multiple systems to search across is the leading obstacle to delivering necessary and timely information to employees, customers, and partners.
Difficulties in searching across systems (56%) was followed closely by problems with information and data silos (55%) and issues with information and data quality (52%) as the leading causes of knowledge friction. Other top obstacles include challenges in finding the correct search terms to locate desired information (46%) and insufficient content sharing (44%).
Knowledge friction can look different and have varying impacts depending on your industry and function. Here are some examples of warning signs to watch out for by department and the negative business outcomes that come with them:
Anyone can increase these truths from their point of need. And these symptoms and impacts are just the tip of the iceberg. The report from Unisphere Research identified 21 risks of stalled access to business-critical information:
Since legacy content management systems and enterprise search engines have fallen short, many enterprises are looking to Knowledge AI to tackle knowledge friction. Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), Knowledge AI swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers. This means no more endless searching through complex systems or wasting time on outdated information. Instead, teams can rely on a Knowledge AI platform for instant access to reliable answers, precisely when they need them.
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.
.png)
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.
.png)
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.
We’ve all felt the pain of needing a quick answer at work and spending hours checking different systems to find it — searching around for the right file, attempting to remember the right keywords to use, trying to get time with an already overburdened SME, and feeling frustrated by a lack of results. Then, once you think you’ve found the content you need, you spend more time reading through it, parsing the information to pinpoint the answer to your question. All the while crossing your fingers that the file is up-to-date and the information inside is verified.
Sound familiar?
You’re not alone. Pryon recently worked with Unisphere Research to survey a cross-industry group of enterprise leaders and knowledge workers on this problem. The survey found that employees waste hours weekly searching for information scattered across the enterprise. Yet, much of an organization’s content still goes unused. More than one out of five respondents estimate that less than half of the unstructured information in their organization is readily available. And only a handful (6%) reported the complete availability of their organization’s information.
1 in 5 enterprise leaders report that less than half of their organization’s content is readily available.
Knowledge friction is the disconnect between enterprise authors and key content consumers. It is a constant consequence to productivity, operations, compliance, and revenue. Content authors — such as marketing, support managers, sales enablement, and product teams — invest high-quality time and effort producing informative content for end users — from salespeople and researchers to operations and customer support teams. Even after all this, end users still struggle to find and access the answers they need.
While organizations invest billions of dollars every year in content management software and enterprise search systems to try and solve their knowledge friction problems, they've seen little to no results. In fact, introducing too many of these systems compounds knowledge friction. The 2024 Survey on Enterprise Information Discovery found that having multiple systems to search across is the leading obstacle to delivering necessary and timely information to employees, customers, and partners.
Difficulties in searching across systems (56%) was followed closely by problems with information and data silos (55%) and issues with information and data quality (52%) as the leading causes of knowledge friction. Other top obstacles include challenges in finding the correct search terms to locate desired information (46%) and insufficient content sharing (44%).
Knowledge friction can look different and have varying impacts depending on your industry and function. Here are some examples of warning signs to watch out for by department and the negative business outcomes that come with them:
Anyone can increase these truths from their point of need. And these symptoms and impacts are just the tip of the iceberg. The report from Unisphere Research identified 21 risks of stalled access to business-critical information:
Since legacy content management systems and enterprise search engines have fallen short, many enterprises are looking to Knowledge AI to tackle knowledge friction. Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), Knowledge AI swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers. This means no more endless searching through complex systems or wasting time on outdated information. Instead, teams can rely on a Knowledge AI platform for instant access to reliable answers, precisely when they need them.
We’ve all felt the pain of needing a quick answer at work and spending hours checking different systems to find it — searching around for the right file, attempting to remember the right keywords to use, trying to get time with an already overburdened SME, and feeling frustrated by a lack of results. Then, once you think you’ve found the content you need, you spend more time reading through it, parsing the information to pinpoint the answer to your question. All the while crossing your fingers that the file is up-to-date and the information inside is verified.
Sound familiar?
You’re not alone. Pryon recently worked with Unisphere Research to survey a cross-industry group of enterprise leaders and knowledge workers on this problem. The survey found that employees waste hours weekly searching for information scattered across the enterprise. Yet, much of an organization’s content still goes unused. More than one out of five respondents estimate that less than half of the unstructured information in their organization is readily available. And only a handful (6%) reported the complete availability of their organization’s information.
1 in 5 enterprise leaders report that less than half of their organization’s content is readily available.
Knowledge friction is the disconnect between enterprise authors and key content consumers. It is a constant consequence to productivity, operations, compliance, and revenue. Content authors — such as marketing, support managers, sales enablement, and product teams — invest high-quality time and effort producing informative content for end users — from salespeople and researchers to operations and customer support teams. Even after all this, end users still struggle to find and access the answers they need.
While organizations invest billions of dollars every year in content management software and enterprise search systems to try and solve their knowledge friction problems, they've seen little to no results. In fact, introducing too many of these systems compounds knowledge friction. The 2024 Survey on Enterprise Information Discovery found that having multiple systems to search across is the leading obstacle to delivering necessary and timely information to employees, customers, and partners.
Difficulties in searching across systems (56%) was followed closely by problems with information and data silos (55%) and issues with information and data quality (52%) as the leading causes of knowledge friction. Other top obstacles include challenges in finding the correct search terms to locate desired information (46%) and insufficient content sharing (44%).
Knowledge friction can look different and have varying impacts depending on your industry and function. Here are some examples of warning signs to watch out for by department and the negative business outcomes that come with them:
Anyone can increase these truths from their point of need. And these symptoms and impacts are just the tip of the iceberg. The report from Unisphere Research identified 21 risks of stalled access to business-critical information:
Since legacy content management systems and enterprise search engines have fallen short, many enterprises are looking to Knowledge AI to tackle knowledge friction. Using cutting-edge technology like natural language processing (NLP) and retrieval-augmented generation (RAG), Knowledge AI swiftly extracts valuable knowledge from existing content, reading it like a human would, and transforming that knowledge into answers. This means no more endless searching through complex systems or wasting time on outdated information. Instead, teams can rely on a Knowledge AI platform for instant access to reliable answers, precisely when they need them.
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.
