AI-Enabled Enterprise Search

We are using this solution to unify multiple systems into a modern search and AI-powered chat tool, providing accurate and up-to-date data that is easily accessible across the lab. The search function leverages natural language processing, dynamic categorization, and summarization to deliver relevant answers to search queries. The underlying data is organized into knowledge collections, allowing for more structured and efficient data retrieval across systems.

• Streamline collections: Organize SLAC data into knowledge collections to simplify retrieval and classification from multiple repositories.
• Improve access: Simplify the retrieval and classification of data from SLAC repositories.
• Enhance search: Use natural language processing for document summaries and related suggestions.
• Secure knowledge sharing: Provide AI-powered chat with verified SLAC-specific information.
• Maintain data privacy: Keep data within its home repository, with access rights intact.
• Continuous improvement: Refine the platform based on feedback during Beta testing.
• Expand use: Apply AI for large-scale data analysis to support specialized areas like Linac Coherent Light Source (LCLS) and Accelerator Directorate (AD).

• Advanced document search: Search documents across repositories with tagging and summarization features, plus suggestions for related content.
• AI chat: Ask questions and get responses based on SLAC-specific data, with references for verification.
• Dynamic categorization: Organize search results to make navigating large volumes of data easier.
• Content guardrails: Customizable content guardrails allow administrators to ensure compliance with SLAC's ethical and governance standards. 
• Role-Based Access Control (RBAC): Efficiently control user permissions with a system tailored to SLAC’s organizational needs.

All documents remain in their original repositories, and SLAC’s access control policies continue to apply. Users may see search results for documents they don’t have permission to access, but only authorized users can open those files, ensuring transparency while maintaining security.

• Support for LCLS and AD: The platform helps manage large text-based data sets, assisting teams in LCLS and AD with data categorization and summarization.
• Expanding knowledge connections: Future expansions will include more SLAC knowledge collections and connections to external DOE knowledge sources.

It is an advanced artificial intelligence platform that leverages Generative AI, Natural Language Understanding (NLU), and Retrieval Augmented Generation (RAG) to enhance enterprise search capabilities. It works by understanding user queries in natural language, retrieving relevant information from internal content repositories, and generating coherent responses to facilitate better information access and communication within an organization.

It improves internal search functionality by using cutting-edge AI algorithms to provide more accurate and relevant search results. It understands the context and nuances of user queries, enabling it to fetch precise information quickly. This reduces the time spent searching for documents and data, thus increasing productivity and efficiency.

It can search through a wide range of content types including documents, emails, internal chat logs, databases, and other digital content repositories. It is designed to integrate seamlessly with various content management systems and databases used within an organization.

Collections ingested into the search platform:

• All internal & public websites

• All SLAC and Stanford Policies

• All IT, Finance and HR Knowledge Base Articles (KBAs)

• DOE Financial Handbook

• SLAC Safety Handbook

• The FAR

• Internal Application content

• Most Confluence Data

• Select GDrive Collections

• Operator Logs

• Non-CUI SharePoint sites

• Engineering Repositories

• Historical Conference Content

• Other documents

Next up:

• DOE DAMAL Data

• Legacy File Storage

• Select Research Data

• Select Operational Data

• Open Slack channels

Yes, AI Enabled Enterprise Search places a high priority on data security. It uses robust encryption methods to protect data during transmission and storage. Additionally, it adheres to strict access control policies to ensure that only authorized personnel can access sensitive information. Regular security audits and updates are conducted to maintain a secure environment.

Feedback and issue reports are essential for success. You can share input or report issues through #slac-it-search-feedback (Slack channel) or the SLAC IT Client Feedback Form. Your contributions will help improve and optimize the AI-enabled Enterprise Search platform.