From Knowledge to Execution: How AI is Revolutionizing Expertise
In every organization, there exists a wealth of untapped expertise—critical knowledge held by subject matter experts (SMEs) that fuels decision-making, operational efficiency, and innovation. Yet, much of this knowledge remains siloed, undocumented, or lost when experienced employees retire or move on.
Traditional knowledge management systems attempt to capture and store this expertise, but they fall short in making it dynamically accessible, actionable, and scalable across the enterprise.
At Keryk, we’ve developed a transformative approach to bridging this gap.
The Pipeline for Integration of Contextual Knowledge (PICK) is an end-to-end AI system that not only captures human expertise but structures, retrieves, and operationalizes it—turning knowledge into real-time execution.
With PICK, businesses can move beyond passive knowledge repositories and build intelligent ecosystems where expertise fuels automation, decision support, and AI-driven execution.
Capturing & Structuring Knowledge at Scale
The foundation of PICK is its ability to extract and organize expertise from multiple sources—from SME interviews and regulatory documents to existing enterprise knowledge bases and real-world operational data. Through AI-powered interviews, deep research agents, and real-time data processing, PICK systematically builds an intelligent knowledge network that retains contextual depth and meaning. This knowledge is structured into a multi-layered AI model, incorporating semantic relationships, ontologies, and vectorized search for seamless retrieval and application.
Rather than relying on rigid, manually updated databases, PICK continuously refines its knowledge base through interaction. It identifies patterns, updates, and inconsistencies, ensuring that the expertise remains current, comprehensive, and aligned with evolving business needs.
AI-Driven Retrieval: Making Expertise Accessible
Once knowledge is captured and structured, the challenge becomes accessibility. In traditional systems, employees struggle to find the right information at the right time, leading to inefficiencies and delays. PICK addresses this through a hybrid AI retrieval model that combines semantic search, knowledge graphs, and contextual AI reasoning to deliver highly relevant, real-time insights.
This enables employees and AI systems to retrieve information naturally and intuitively, whether through chatbots, conversational AI assistants, or direct API integrations into enterprise tools like Salesforce, ServiceNow, and Jira. Instead of keyword searches that yield generic results, users can ask complex, context-aware questions and receive precise, expert-backed answers—mirroring the experience of consulting a live SME.
From Knowledge to Execution: AI-Powered Automation
Once knowledge is captured and structured, the challenge becomes accessibility. In traditional systems, employees struggle to find the right information at the right time, leading to inefficiencies and delays. PICK addresses this through a hybrid AI retrieval model that combines semantic search, knowledge graphs, and contextual AI reasoning to deliver highly relevant, real-time insights.
This enables employees and AI systems to retrieve information naturally and intuitively, whether through chatbots, conversational AI assistants, or direct API integrations into enterprise tools like Salesforce, ServiceNow, and Jira. Instead of keyword searches that yield generic results, users can ask complex, context-aware questions and receive precise, expert-backed answers—mirroring the experience of consulting a live SME.
From Knowledge to Execution: AI-Powered Assistants & Apps
While accessibility is a critical step, PICK goes further by enabling AI-driven execution. Instead of stopping at providing knowledge, PICK uses AI Architect Agents to analyze structured expertise and identify opportunities for AI-powered Apps. This means that repetitive, knowledge-intensive tasks that traditionally required human intervention can now be executed autonomously—while remaining fully aligned with SME best practices and business rules.
For example, in industries with complex compliance requirements, PICK can not only retrieve regulatory guidelines but also create agents that ensure adherence. In operational environments, it can assist field technicians with real-time AI-generated troubleshooting procedures, reducing downtime and increasing efficiency. In corporate settings, AI-driven agents can perform data analysis, reporting, and decision-making support, accelerating processes that once took hours or days.
Measuring Business Impact with Real-Time Visibility
A key advantage of PICK is its built-in executive dashboard, which provides real-time monitoring of AI-driven knowledge usage, automation execution, and business impact.
Decision-makers gain a clear view of how AI is being used across the organization, where it is delivering measurable efficiencies, and how knowledge is evolving over time. T
he system also includes feedback loops, ensuring that AI models continuously improve based on human validation and real-world usage.
Why Organizations Choose PICK
PICK is designed for seamless enterprise integration, providing a secure, scalable, and highly adaptable AI-driven knowledge system. Organizations choose PICK because it allows them to:
- Eliminate Knowledge Silos – Centralizing expertise and making it instantly available across teams.
- Accelerate AI Transformation – Deploying AI-powered automation that enhances human capabilities.
- Enhance Decision-Making – Providing real-time, expert-backed insights for strategic and operational actions.
- Increase Productivity & Efficiency – Reducing the manual effort required to find, interpret, and apply expert knowledge.
- Future-Proof Institutional Knowledge – Ensuring that critical expertise remains available even as workforces change.
With PICK, businesses no longer have to choose between AI and human expertise—they can leverage both, in an intelligent and scalable way.