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Cloud deployment platform for developers that auto-detects code and frameworks to ship apps, servers, and AI-hub services with one push.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
AI-driven platform to visually design multi-cloud infrastructure and auto-generate Terraform code with built-in CI/CD.
Documentation and knowledge platform that keeps developer docs self-updating and queryable by AI agents.
Free trial available
Free trial available
Free trial available
Free trial available
- ✦Automatic language and framework detection and deployment
- ✦Git-push CI/CD with zero configuration
- ✦Auto-scaling compute resources
- ✦Built-in object storage similar to S3
- ✦One-click managed VPS purchase
- ✦Unified AI Hub API for multiple AI models
- ✦Domain and DNS management
- ✦In-browser file management console
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- ✦Python-native dynamic workflow authoring
- ✦Automatic failure recovery, caching, and versioning
- ✦Zero Trust architecture keeping data inside customer's cloud
- ✦Real-time inference and agentic-AI workflow support
- ✦High-throughput scaling (tens of thousands of actions per run)
- ✦Local development environment matching production behavior
- ✦Visual multi-cloud architecture designer
- ✦Instant Terraform/OpenTofu code generation
- ✦Drift detection and remediation
- ✦Embedded visual CI/CD engine
- ✦GitOps workflow and RBAC
- ✦AI infrastructure generation from prompts
- ✦Self-updating documentation
- ✦Web-based documentation editor
- ✦Custom domain hosting
- ✦Built-in search and API playground
- ✦MCP server for agent access
- ✦Authentication and access controls
- →Developers deploying apps without manual server config
- →Teams wanting predictable, fixed-plan hosting costs
- →Startups needing quick CI/CD pipelines
- →Projects needing bundled AI model access alongside hosting
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms
- →ML teams orchestrating training and inference pipelines at scale
- →Biotech/geospatial companies needing GPU-heavy pipeline orchestration
- →Enterprises migrating off Airflow for ML workflow management
- →Teams requiring workflows that never send data outside their own cloud
- →Designing and deploying cloud infrastructure visually
- →Migrating to Infrastructure as Code
- →Standardizing Terraform modules and naming
- →Detecting drift between design and live cloud
- →Publish and maintain developer documentation
- →Expose docs to AI agents via MCP
- →Host a branded docs site on a custom domain
- →Give teams a collaborative doc editor