Overview

Discover AI Knowledge, the product for connecting AI to the expertise and information of your organization

AI Knowledge enables organizations to create AI agents that leverage their unique expertise, documents, and information. Using Retrieval Augmented Generation (RAG), AI Knowledge connects language models to your specific knowledge, allowing them to provide accurate, contextual responses based on your organization’s content.

Key Features

Knowledge Base Creation

Build searchable repositories of your organization’s information

Document Management

Upload, process, and organize documents across formats

RAG Configuration

Fine-tune how AI accesses and uses your knowledge

Agent Creation

Build specialized agents powered by your knowledge

Testing & Validation

Verify accuracy and relevance of responses

Tool Integration

Extend capabilities with specialized tools

Performance Analytics

Track knowledge retrieval effectiveness

Continuous Improvement

Refine and optimize knowledge access over time

Who Uses AI Knowledge?

AI Knowledge serves various roles within organizations:

Knowledge Managers

Information specialists and knowledge managers use AI Knowledge to:

• Organize and structure organizational knowledge
• Create accessible knowledge bases
• Maintain and update information
• Monitor knowledge usage and gaps

Subject Matter Experts

Domain experts use AI Knowledge to:

• Capture and share specialized expertise
• Build agents that reflect their knowledge
• Answer common questions in their field
• Scale their impact across the organization

Business Teams

Functional departments use AI Knowledge to:

• Create specialized agents for their domain
• Provide consistent information to stakeholders
• Reduce repetitive questions and inquiries
• Preserve institutional knowledge

IT & Developers

Technical teams use AI Knowledge to:

• Configure and optimize knowledge retrieval
• Integrate knowledge agents with existing systems
• Build custom tools and extensions
• Implement advanced RAG architectures

How AI Knowledge Works

1. Document Ingestion

   Upload and process your organization’s documents and content.

   AI Knowledge supports various document types including:

   • PDF files
   • Word documents
   • PowerPoint presentations
   • Excel spreadsheets
   • HTML content
   • Text files
   • Images with text (via OCR)
   • And more
2. Knowledge Processing

   Documents are processed, chunked, and converted into embeddings.

   Processing includes:

   • Text extraction
   • Semantic chunking
   • Vector embedding generation
   • Metadata extraction
   • Optional content enrichment
3. Knowledge Base Creation

   Organize and structure processed documents into searchable knowledge bases.

   Knowledge bases can be:

   • Topic-specific
   • Department-focused
   • Project-based
   • Product-centered
   • Audience-targeted
4. Agent Configuration

   Connect knowledge bases to AI agents and fine-tune retrieval settings.

   Configuration includes:

   • RAG parameters
   • Context handling
   • Query processing
   • Response generation
   • Tool integration
5. Deployment & Use

   Make knowledge-powered agents available to users through various channels.

   Deployment options:

   • AI Store listing
   • Direct sharing
   • Integration into applications
   • API access
   • Embedded experiences
6. Monitoring & Optimization

   Track performance and continuously improve knowledge retrieval.

   Key metrics include:

   • Retrieval accuracy
   • Query coverage
   • User satisfaction
   • Knowledge gaps
   • Response quality

RAG Overview

Retrieval Augmented Generation (RAG) is the core technology behind AI Knowledge:

What is RAG?

RAG combines retrieval systems with generative AI to produce responses grounded in specific knowledge:

1. A user query is processed to understand the information need
2. Relevant documents or passages are retrieved from knowledge bases
3. Retrieved information is provided as context to the language model
4. The model generates a response that incorporates this specific knowledge

This approach ensures AI responses are:

• Grounded in accurate, up-to-date information
• Specific to your organization’s context
• Properly attributed to sources
• Less prone to hallucination or fabrication

Benefits of RAG

Using RAG through AI Knowledge provides several advantages:

• Knowledge Recency: Access the latest information, beyond the model’s training cutoff
• Factual Grounding: Base responses on verified organizational knowledge
• Reduced Hallucinations: Minimize fabricated or incorrect information
• Domain Specificity: Provide expertise in your organization’s unique areas
• Source Attribution: Trace responses back to specific documents and sources
• Knowledge Control: Determine exactly what information the AI can access and use
• Compliance Support: Ensure responses adhere to organizational policies and standards

Knowledge Base Types

AI Knowledge supports different types of knowledge bases to meet various needs:

Document Repositories

Collections of structured documents like manuals, reports, and policies

FAQ Collections

Frequently asked questions with curated answers

Product Knowledge

Information about products, specifications, and features

Procedural Guides

Step-by-step instructions and processes

Technical Documentation

Technical details, APIs, and system information

Training Materials

Educational content and learning resources

Research Collections

Scientific papers, studies, and findings

Legal & Compliance

Regulations, policies, and compliance information

Integration with Prisme.ai Products

AI Knowledge works seamlessly with other Prisme.ai products:

Product	Integration
AI SecureChat	Access knowledge bases through conversational interface
AI Store	Share and discover knowledge-powered agents
AI Collection	Combine structured and unstructured data access
AI Builder	Create advanced applications with knowledge integration
AI Governance	Manage access and security for knowledge resources
AI Insights	Track performance of knowledge-based interactions

Getting Started with AI Knowledge

1. Access AI Knowledge

   Navigate to AI Knowledge from your Prisme.ai dashboard.

2. Create your first knowledge base

   Click “Create Knowledge Base” to begin the setup process.

   Follow the guided process to:

   • Name your knowledge base
   • Define its purpose
   • Set access permissions
   • Configure basic settings
3. Upload initial documents

   Add documents to your knowledge base.

   You can:

   • Upload files directly
   • Connect to document repositories
   • Import from URLs
   • Use the document processing API
4. Configure basic RAG settings

   Set up how your knowledge will be processed and retrieved. Start with recommended settings for:

   • Chunking strategy
   • Retrieval method
   • Context handling
   • Response generation
5. Create a knowledge agent

   Build an agent that uses your knowledge base.

   Define:

   • Agent purpose and behavior
   • Knowledge base connections
   • Response preferences
   • User interaction style
6. Test and refine

   Try out your agent and adjust settings as needed.

   The testing interface allows you to:

   • Ask sample questions
   • View retrieved contexts
   • Evaluate response quality
   • Identify areas for improvement

Use Cases

Internal Knowledge Management

Create agents that help employees find and use company policies, procedures, and best practices.

Example:

HR Policy Assistant that answers questions about benefits, time off, and workplace policies.

Technical Support

Build agents that assist with troubleshooting, maintenance, and technical information.

Example:

Product Support Agent that helps customers resolve issues with specific products.

Research Assistance

Develop agents that help analyze and extract insights from research collections.

Example:

Research Assistant that helps scientists navigate relevant papers and studies.

Training & Onboarding

Create agents that help with learning and skill development.

Example:

Onboarding Assistant that guides new employees through company systems and processes.

Sales & Marketing Support

Build agents that provide accurate product information and marketing content.

Example:

Product Knowledge Agent that helps sales teams access accurate specifications and features.

Compliance & Legal

Develop agents that help navigate complex regulatory and legal requirements.

Example:

Compliance Assistant that provides guidance on industry regulations and internal policies.

Next Steps

Explore more detailed guides for AI Knowledge features:

Knowledge Bases

Create and manage collections of organizational knowledge

Document Management

Upload, process, and organize documents

Create Knowledge Base

Step-by-step guide to building your first knowledge base

RAG Configuration

Fine-tune retrieval and response settings

Analytics

Track and improve knowledge base performance

Tools Integration

Enhance agents with specialized capabilities

Agent Testing

Validate and improve agent responses

Advanced RAG

Implement sophisticated RAG architectures