How AI is set to democratize information [Q&A]

One of the features of AI is its ability to process large volumes of data to identify patterns and make information more accessible.

We spoke to Igor Jablokov, CEO and founder of Pryon, about how enterprises can take advantage of this ability and make better use of their data.

BN: You've referred in the past to the future of AI as a 'knowledge cloud' that would democratize access to information. Can you elaborate on that?

IJ: The concept of AI as a 'knowledge cloud' is directly tied to information access and organizational intelligence. It's essentially an interconnected network of systems of records forming a centralized repository of insights and lessons learned, accessible to individuals and organizations. At its core, this AI-driven knowledge cloud would integrate vast amounts of data from diverse internal and external sources, utilize advanced algorithms for processing and analysis, and feature intuitive natural language interfaces, all while continuously learning and updating itself.

One of the most transformative aspects of this concept is its potential to democratize access to information. By breaking down barriers to knowledge, the AI knowledge cloud could eliminate the need for specialized expertise to interpret complex information, providing instant access to a wide range of topics and fields. This leveling of the playing field could grant individuals and smaller organizations access to insights that were previously available only to large corporations or institutions, potentially reducing the advantage of those with privileged access to information. Additionally, the system could offer personalized learning experiences and problem-solving capabilities, tailoring information delivery to individual needs and providing context-aware solutions to specific questions or challenges.

BN: What impact would broader access to information have on organizations?

IJ: It would enable any entity to become an intelligence agency and prompt a fundamental shift in how they operate. With access to real-time, data-driven insights, organizations could significantly enhance their decision-making capabilities, rapidly analyzing complex situations and predicting outcomes. This could lead to improved operational efficiency by automating routine information gathering and analysis tasks, freeing up human resources for higher-level thinking and creativity.

Organizations could gain a competitive edge through a deeper understanding of customers, markets, and trends, allowing them to identify opportunities and threats more accurately and quickly. This shared knowledge could also facilitate cross-functional collaboration, breaking down information silos within organizations and enabling interdisciplinary problem-solving.

BN: Can you elaborate on the concept of 'knowledge friction' and why it's a problem for enterprises?

IJ: Knowledge friction is a pervasive issue in modern enterprises, stemming from the lack of an accessible and unified source of information. Historically, organizations have never had a singular repository for all their knowledge and data, akin to libraries in academic or civic communities. Instead, enterprise knowledge is scattered across numerous platforms and systems -- each managed by different vendors, operating in silos. This fragmentation causes significant friction, as employees across all levels and departments struggle to find the information they need quickly and efficiently to do their jobs.

Pryon identified this friction as a critical bottleneck in organizational efficiency and saw an opportunity to introduce a transformative solution. The concept behind Pryon is to create a new layer above the traditional enterprise software stack, which unifies these disparate systems. By using natural language prompts, Pryon's AI-enhanced knowledge cloud can traverse various systems of record and retrieve diverse types of data -- whether it's text, images, videos, structured or unstructured data -- at remarkable speed, typically in under a second. This capability reduces the time and effort employees spend searching for information, thereby increasing productivity and enabling more informed decision-making.

Pryon marks a significant leap forward in how enterprises manage and utilize their collective knowledge. By centralizing and simplifying access to information, our platform eliminates the barriers that traditionally hindered seamless knowledge sharing across an organization. In essence, Pryon enables a frictionless flow of knowledge, which is crucial for the agility and competitiveness of modern enterprises in an increasingly data-driven world.

BN: What's the solution to making knowledge accessible?

IJ: It involves an automated multi-phase process that leverages advanced AI technologies to transform vast amounts of data into actionable insights.

First, the process begins with an ingestion pipeline that collects data from a wide range of sources, such as enterprise systems, content management platforms, and other repositories. This data can be in various formats, including text, audio, video, images, PowerPoint presentations, PDFs, and web pages. The ingestion phase is essential for gathering and normalizing diverse data types, ensuring that all relevant information is captured and ready for further processing.

Next, the data moves through a retrieval pipeline designed to accurately and efficiently extract the most relevant information from the ingested content. This step is crucial for making sure users can quickly access the pertinent data they need from large volumes of stored content. The retrieval pipeline is optimized to find and present the right information, making it easily accessible for users to act upon.

Finally, the data is processed through a generative pipeline, where advanced AI techniques, including large language models (LLMs), are employed to generate targeted responses or actions based on the retrieved information. This phase allows the system not only to present existing information but also to synthesize the data to create new insights or recommendations.

By integrating these phases into easy to digest user experiences, organizations can make their knowledge accessible, allowing users to quickly find and use the information they need in a meaningful way.

BN: How does Pryon specifically solve this problem?

IJ: Pryon is built on the pillars stated above. The platform is designed with enterprise-grade accuracy, scalability, security, and speed at its core, making it particularly well-suited for large-scale environments. These capabilities are supported by Pryon's robust Retrieval-Augmented Generation (RAG) framework, which enhances the platform's ability to deliver precise, timely answers.

• Accuracy: Pryon excels in accuracy by meticulously ingesting and understanding content across various formats, including text, images, audio, and video. The platform uses advanced, custom-developed technologies to ensure that the information retrieved is not only relevant but also reliable and verifiable, with over 90 percent accuracy in mission-critical knowledge retrieval. This high level of precision is essential for enterprises that rely on accurate data to make informed decisions.
• Scalability: Pryon is built to handle the vast scale typical of large enterprises. The platform can scale to manage millions of pages of content and support thousands of concurrent users without compromising performance. Moreover, Pryon offers out-of-the-box connectors to major platforms like SharePoint, ServiceNow, Amazon S3, and Box, facilitating easy integration into existing workflows and systems.
• Security: Security is a top priority for Pryon, particularly given the sensitive nature of the data handled by large enterprises. The platform employs document-level access controls to prevent data leaks and ensures that AI models are not trained on customer data, maintaining confidentiality and integrity. Additionally, Pryon can be deployed in on-premises environments, providing organizations with an extra layer of security and control over their data.
• Speed: Speed is another critical factor, and Pryon delivers rapid deployment with implementation possible in as little as two weeks. The platform’s no-code interface allows for quick and easy content updates, ensuring that enterprises can respond rapidly to changing needs. Pryon also offers the flexibility to choose between public, custom, or Pryon-developed large language models (LLMs), enabling seamless and highly customizable AI deployments.

These pillars are precisely why Pryon is trusted by academic institutions, Fortune 500 companies, government agencies, and NGOs in sectors like defense, energy, financial services, and semiconductors.

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