This guide covers eGain Composer, a comprehensive AI-powered knowledge management and retrieval engine that enables intelligent content discovery, agentic workflows, and personalized user experiences across multiple interfaces. It outlines how you, as a developer, can interact with eGain’s services—from ingestion to delivery—across various channels such as web portals, help centers, and conversational apps.
The platform ingests content from three primary sources:
- Conversations: User interactions, call and chat transcripts
- Content: Documents, articles, and media files
- Data: Structured datasets and databases
These sources feed into a centralized Content/Data Lake that serves as the foundation for all downstream services.
- Purpose: Centralized repository for all ingested content and data
- Features:
- Scalable storage for multi-format content
- Data preprocessing and normalization
- Version control and content lifecycle management
- Integration: Feeds processed content to retrieval engine
- Purpose: Intelligent content discovery and matching engine
- Capabilities:
- Vector-based semantic search
- Hybrid search combining keywords and embeddings
- Real-time indexing and updates
- Relevance scoring and ranking
- Output: Provides relevant content chunks to downstream APIs
- Purpose: AI-powered autonomous applications that can take actions
- Features:
- Goal-oriented task execution
- Multi-step reasoning and planning
- Integration with external tools and services
- Context-aware decision making
Key Features:
- Bulk Content Import: Import large volumes of content from legacy knowledge management system
- Content Validation: Pre-import validation to ensure content quality and compliance
- Job Management: Track and manage import operations with detailed status monitoring
- Scheduling: Schedule imports for off-peak hours to minimize system impact
- Real-time Monitoring: Monitor import progress and access detailed logs
Key Features:
- Access Controlled View: Role-based permissions and content filtering
- Personalized: User-specific content recommendations and customization
- Event-driven: Real-time updates and notifications
Key Features:
- Content-aware Retrieval: Understanding of document structure and context
- Chunks or Articles: Flexible granularity for search results
- Relevance Rank: Advanced scoring algorithms
Key Features:
- Consumable: Ready-to-use formatted responses
- Best Answer: Quality-ranked response selection
- Source(s) Attribution: Transparent citation and provenance
Key Features:
- Conversational Turns: Multi-turn dialogue management
- Global Context: Persistent memory across sessions
- Guided Actions: Structured workflows and decision trees
Target Users: Agents, Customers, and Employees
Features:
- Web Page: Responsive web interface
- Personalized: Driven by user permissions, scopes, and preferences
- Configurable Content/Look: Themeable UI and layout options
Target Users: End users seeking interactive AI assistance
Features:
- Widget/Chatpage: Embeddable chat interfaces
- Personalized: Context-aware conversations
- Configurable Experience: Customizable chat flows and responses