AutoWorkflow bridges the gap between fragmented SaaS tools and intelligent LLM logic. Build, test, and deploy production-ready automations in minutes, powered by a global event-driven backbone on AWS infrastructure.
Respond to any event from 500+ integrations instantly using our high-performance AWS EventBridge integration.
Handle complex business logic with visual state machines built on AWS Step Functions, supporting infinite retries and error handling.
Enterprise-grade credential management using AWS Secrets Manager. Your API keys are encrypted and never exposed.
Harness the power of multiple AI models for intelligent workflow decisions, seamlessly integrated with Amazon Bedrock.
Integrate with GPT-4, Claude, Llama 3, and other leading LLMs for diverse reasoning capabilities.
Leverage AWS's native AI service for secure, scalable access to foundation models.
Process unstructured data and make context-aware decisions beyond simple IF-THEN logic.
Our workflow engine is designed for mission-critical operations, ensuring 99.99% uptime for your automated processes.
Massive scale webhook handling via Amazon API Gateway and SQS.
Dynamic data transformation using Amazon Bedrock models.
Built on AWS's global cloud infrastructure for unlimited scalability and reliability.
Automatically scale resources up or down based on workflow demand using AWS Auto Scaling.
Deploy workflows across multiple AWS regions for low latency and disaster recovery.
Integrate AutoWorkflow into your existing stack with our RESTful API and lightweight SDKs.
// Initialize Workflow
const flow = new AutoWorkflow({
apiKey: process.env.AW_KEY,
region: 'us-east-1'
});
// Trigger automated sequence
await flow.trigger('order_paid', {
customer_id: 8829,
auto_invoice: true
});
Comprehensive resources for developers to build and integrate workflows with AutoWorkflow.
Detailed documentation for all API endpoints, request/response formats, and authentication methods.
Explore API DocsOfficial SDKs for Python, JavaScript, and Go, with code examples and integration guides.
View SDKsReady-to-use workflow templates for common business scenarios and use cases.
Browse ExamplesPowering high-demand workflows that require massive computational resources and intelligent processing.
Process millions of unstructured documents with AI-powered extraction and analysis using Amazon S3 for storage and Amazon Bedrock for LLM inference.
Handle high-throughput streaming data pipelines with Amazon Kinesis and AWS Lambda, processing events in real-time with sub-second latency.
Run secure, scalable LLM fine-tuning pipelines on Amazon SageMaker with custom datasets, deploying models to private endpoints for enterprise use.
AutoWorkflow is scaling its global infrastructure to support over 1 billion events monthly. We are currently utilizing AWS Fargate for serverless compute and Amazon Aurora Serverless for dynamic data scaling.
Automatically scale resources based on workflow demand, leveraging AWS Auto Scaling and elastic container services for optimal performance.
Enterprise-grade security using AWS security groups, encryption at rest with KMS, and Secrets Manager for credential protection.
Pioneering AI-driven workflow automation by integrating large language models through Amazon Bedrock for intelligent decision-making.
Complete integration with AWS's native AI service for seamless access to foundation models.
Deploy infrastructure across 5 AWS regions for reduced latency and improved redundancy.
Launch custom model training pipelines on Amazon SageMaker for industry-specific workflows.
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