Core Platform Concepts
Document Processing & AI Integration
- Documents are parsed into standardized structures that can be processed by various AI models
- Generative AI capabilities are deeply integrated to handle unstructured data, tabular content, and even low-quality scans
- The platform is model vendor-agnostic, allowing you to use the best AI models for specific use cases
- Built-in guardrails ensure data lineage and quality
Task-Based Architecture
The platform is built around the concept of Tasks, which provide:- A framework for AI/human collaboration
- Context for processing multiple related documents
- Integration points for workflow management
- Support for comments, assignments, and progress tracking
Infrastructure Components
Core Services
- Operational Data Store for managing metadata, lineage, and orchestration
- Event-bus infrastructure for scalable processing
- S3-based Storage Layer for Data Lake capabilities
- OpenSearch Index Services for monitoring and reporting
Developer Tools
- RESTful API supporting all platform capabilities
- Python SDK for easy integration
- Studio interface for designing, testing, and debugging implementations
- Workflow interface for managing human-in-the-loop tasks
Platform Features
- Rich Human-in-the-Loop tools with feedback mechanisms
- Powerful validation and rules engine
- Comprehensive logging and analytics
- Blue/Green deployment support for AI models
- Event-based processing architecture