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Riptide Workflow Engine

Overview

The Riptide Workflow Orchestration Engine is an enterprise-grade platform designed for automated document processing, AI-powered data extraction, and complex business process automation. Built on clean architecture principles with asynchronous execution and distributed job processing, it supports thousands of concurrent workflow executions with horizontal scaling, comprehensive observability, and flexible integration with AI models and business systems.

Why Riptide Workflow Engine

The Riptide Workflow Engine delivers enterprise-scale automation with support for thousands of workflows per day, horizontal scaling across multiple worker instances, and distributed job processing. Every workflow execution is fully traceable with correlation IDs, execution history, and comprehensive audit trails for compliance and debugging.

AI integration transforms processing workflows through seamless integration with models such as Azure AI, OpenAI, Anthropic Claude, and locally hosted models running on Ollama, vLLM, or other infrastructure. The engine abstracts AI provider complexity through named model interfaces managed by administrators, allowing workflow designers to select and use AI capabilities without managing technical endpoints or API keys.

Business agility increases through workflow definitions that can be designed visually in the workflow-designer tool, tested, and deployed rapidly. Modify process logic, update AI prompts, or adjust routing decisions without code changes—often deploying new workflows in hours rather than weeks.

Operational efficiency improves with email-based human task orchestration, configurable work queues with priorities and SLAs, and automatic escalation. The platform provides real-time visibility with execution status, node-level history, and performance metrics.

Developer productivity accelerates with clean architecture separating domain logic from infrastructure, pluggable node implementations, and DynamicExpresso for dynamic C# expression evaluation in decision nodes. The engine integrates seamlessly with the Riptide SDK for identity management, logging, and platform services.

Flexible execution patterns support synchronous and asynchronous workflows, scheduled execution via cron triggers, automatic retry policies with configurable attempts and delays, and result archival to maintain database performance at scale. Complete observability through OpenTelemetry distributed tracing, health checks, and Prometheus metrics ensures production reliability.

Purpose

Modern document processing and business automation requires orchestrating complex interactions between file systems, databases, AI models, human reviewers, and notification systems. The Riptide Workflow Engine solves this by:

  1. Providing visual workflow design with JSON-based definitions that integrate seamlessly with the workflow-designer tool
  2. Supporting asynchronous execution at scale with reliable background job processing
  3. Abstracting AI model complexity through named interfaces that business users can reference without technical knowledge
  4. Enabling human-in-the-loop workflows with email-based task orchestration, work queues, and secure callbacks
  5. Integrating with diverse data sources through SQL query nodes, file download nodes, and PDF processing capabilities
  6. Maintaining complete execution history with automatic archival for performance and compliance

Key Capabilities

The Riptide Workflow Engine uses JSON-based workflow definitions designed in the visual workflow-designer tool and deployed via REST API. Workflows define nodes (tasks), edges (connections), and execution logic in a declarative format that supports versioning, import/export, and validation before deployment.

AI-powered extraction is central to the engine's document processing capabilities. The platform supports multiple AI providers through a unified interface. Business administrators configure named model interfaces like "Local Vision Model" or "Claude Document Processing". Workflow designers then reference these by name without managing endpoints, API keys, or model parameters.

Asynchronous execution architecture provides distributed job processing with persistent storage, automatic retry, and priority queues. The REST API accepts workflow execution requests and immediately returns a tracking ID while the engine processes nodes in the background across horizontally scaled worker instances.

Human task orchestration pauses workflows for manual intervention through email notifications with secure callback links. Business-configurable work queues (Expedite, Same-Day, General, Finance, HR, etc.) have assigned priorities, SLAs measured in hours, and designated teams. Tasks remain valid until SLA expiration, ensuring accountability and preventing unauthorized completions.

Advanced workflow patterns include SQL query nodes for database operations, file download nodes supporting Azure Blob Storage and HTTP endpoints, PDF processing nodes for page extraction and manipulation, decision nodes for dynamic expression evaluation, transform nodes for JSON data manipulation, and notification nodes for email, SMS, webhooks, Teams, and Slack.

Complete observability tracks every node execution with inputs, outputs, duration, and errors. Correlation IDs link related operations across distributed systems for complete traceability. The engine provides health check endpoints, metrics collection, and execution history APIs for real-time monitoring and troubleshooting.

Workflow Orchestration System

The Riptide Workflow Engine supports sophisticated automation patterns. SQL Query Nodes execute parameterized queries against business databases, supporting INSERT, UPDATE, DELETE, and SELECT operations with dynamic parameter binding from workflow context variables.

File Download Nodes retrieve documents from Azure Blob Storage, HTTP/HTTPS endpoints, and local file system paths with flexible authentication options. PDF Processing Nodes extract specific pages, split documents into individual pages, merge multiple PDFs, and extract metadata for downstream processing.

AI Extraction Nodes send documents or images to configured model interfaces with custom prompts and field definitions. The engine manages provider-specific request formats, authentication, rate limiting, and error handling—returning normalized results with confidence scores and extracted field values.

Decision Nodes evaluate dynamic expressions at runtime, routing workflows based on confidence scores, field values, business rules, or any condition expressible through the expression engine. Transform Nodes manipulate JSON data structures, mapping fields, aggregating values, and preparing data for subsequent nodes.

Human Task Nodes pause execution and generate email notifications with customizable templates, placeholder substitution for task details and due dates, and secure callback URLs. The engine validates callbacks, checks expiration against SLA deadlines, and resumes workflow execution when users complete tasks.

Notification Nodes send alerts via email, SMS, webhooks to external systems, and chat platforms including Microsoft Teams and Slack. Error handling supports automatic retry with configurable attempts, custom error routes in workflow definitions, and manual intervention when automatic recovery is exhausted.

Integration Points

Applications interact with the Workflow Engine through a REST API that creates workflow definitions, starts executions, queries instance status, retrieves execution history, manages human tasks, and cancels running workflows. The API supports import/export of workflow definitions from the visual workflow-designer tool for seamless deployment.

Configuration management uses a hybrid approach: workflows, work queues, and AI model interfaces can be seeded from configuration files on startup and then managed through admin APIs. This enables version-controlled configuration in development while supporting dynamic updates in production without redeployment.

Database architecture separates business data from workflow engine data. Business databases contain application-specific tables accessed via SQL Query Nodes, while the workflow engine database stores execution state, job queue data, human tasks, and configuration. This separation enables independent scaling and backup strategies.

Riptide SDK integration provides identity management for authentication and authorization, structured logging with correlation IDs, configuration management with environment-specific overrides, and health check patterns for monitoring. The engine leverages SDK abstractions for consistent behavior across the Riptide platform.

Container deployment supports containerization with flexible migration strategies, health check endpoints for orchestration integration, metrics export, and horizontal scaling through multiple worker instances sharing a common database.

Scheduled execution supports recurring workflows with flexible scheduling, one-time scheduled executions with start date/time, and timezone-aware scheduling across multiple regions. Event-driven triggers can initiate workflows from external systems via webhook endpoints with configurable authentication.

Common Use Cases

Organizations use the Riptide Workflow Engine to automate document-intensive and AI-powered business processes. PDF document processing workflows download documents from storage, extract specific pages, send images to AI models for stamp detection and field extraction, route low-confidence results to human reviewers in work queues, and save validated data to business databases—all without manual intervention until human judgment is required.

AI-powered data extraction handles forms, invoices, contracts, and government documents by routing images through appropriate AI models, validating confidence scores through decision nodes, and escalating uncertain extractions to work queues with appropriate SLAs and team assignments.

Multi-stage review workflows coordinate document intake, automated field extraction via AI, confidence-based routing to expedite or standard review queues, parallel review when multiple approvals are required, and final disposition with notification to stakeholders—maintaining complete audit trails for compliance and quality assurance.

Scheduled batch processing runs nightly workflows to process accumulated documents, calculate fees based on extracted data, update business databases with processing results, archive completed workflows automatically, and send summary notifications to operations teams—enabling lights-out processing at enterprise scale.

Human-in-the-loop automation blends AI extraction with human verification by sending documents to AI models first, evaluating confidence scores to determine when human review is needed, routing tasks to appropriate work queues based on document type or priority, and resuming automated processing after human validation—achieving optimal balance between automation and accuracy.

Cross-system orchestration coordinates activities across document storage, AI providers, business databases, email systems, and chat platforms—breaking down integration complexity through declarative workflow definitions and unified execution monitoring.

Technical Specifications

  • Platform: .NET 8.0 with REST API
  • Architecture: Clean architecture with domain-driven design and pluggable node implementations
  • Background Processing: Distributed job queue with persistent storage, automatic retry, and priority queues
  • Expression Evaluation: Dynamic expression evaluation in decision nodes
  • Data Storage: Separate databases for business data and workflow engine data with flexible database support
  • Authentication: Riptide SDK Identity integration with role-based access control
  • Deployment: Container-based deployment with health checks and horizontal scaling support
  • API Documentation: Comprehensive REST API documentation
  • Monitoring: Distributed tracing, metrics collection, health check endpoints, and execution history APIs
  • Performance: Designed for thousands of workflows per day with horizontal scaling
  • Security: Signed callback URLs, encrypted credentials, and comprehensive audit logging
  • Archival: Automatic archival of completed workflows with configurable retention for compliance

Roadmap

The Riptide Workflow Engine roadmap focuses on enhancing the visual design experience, expanding AI capabilities, and improving operational visibility:

Phase 1 (Current Release)

  • Core workflow engine with asynchronous execution
  • All essential node types: SQL Query, File Download, PDF Processing, AI Extraction, Decision, Human Task, Notification, Transform
  • Email-based human tasks with secure callbacks
  • Business-configurable work queues with priorities and SLAs
  • Admin-managed AI model interfaces for provider abstraction
  • Container-based deployment
  • Scheduled execution support
  • Automatic result archival with configurable retention

Phase 2 (Enhanced Designer & Monitoring)

  • Enhanced workflow-designer UI with improved visual design capabilities
  • Real-time execution monitoring dashboard showing active workflows and node status
  • Advanced human task UI with embedded forms and document viewers
  • Workflow analytics and reporting with performance metrics and bottleneck identification
  • Multi-tenant support enhancements for SaaS deployments
  • Parallel node execution for concurrent processing
  • Sub-workflow support for reusable process components

Phase 3 (Marketplace & Intelligence)

  • Workflow marketplace with pre-built templates for common use cases
  • Advanced AI model routing with fallback chains and cost optimization
  • Real-time collaboration features for workflow design teams
  • Workflow templates library with industry-specific patterns
  • Enhanced error recovery with automatic compensation logic
  • Business calendar integration for deadline calculations
  • Advanced API capabilities for flexible querying and real-time subscriptions