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Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
Agentic AI SRE using dynamic code analysis to find, root-cause, and remediate code and infrastructure issues before production.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
Free trial available
Free trial available
No public pricing
- ✦One-command deploy from Docker Compose
- ✦Deploys into your own or a customer's cloud account
- ✦Native managed LLM access (Bedrock/Vertex/Azure AI)
- ✦Managed Postgres, MongoDB and Redis
- ✦Auto-configured IAM, VPC, TLS and load balancing
- ✦Open-source CLI and cloud providers
- ✦Dynamic Code Analysis engine
- ✦Automated root-cause analysis and remediation
- ✦Pull-request and config fix suggestions
- ✦MCP server for AI-assisted code review
- ✦Observability and data-source integrations
- ✦Runs locally or on-prem/private cloud
- ✦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
- ✦Automated service discovery and dependency topology mapping
- ✦SLO-based alert triage and prioritization
- ✦AI-driven root cause analysis with pre-built workflows
- ✦Human-approved remediation with full audit trails
- ✦Works alongside existing tools like Datadog, Grafana, New Relic
- ✦Governance and policy enforcement layer for agent actions
- →Shipping AI agents and web apps to production
- →Deploying the same app across many customer clouds
- →Agencies deploying into client cloud accounts
- →Avoiding hand-written Terraform or Kubernetes
- →Reducing incident resolution time
- →Catching performance issues pre-production
- →Enhancing AI code reviews with runtime data
- →Monitoring microservice performance
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms
- →SRE teams reducing mean-time-to-resolution during incidents
- →Platform engineers wanting policy-governed AI infrastructure management
- →Enterprises needing SOC 2 / PCI / HIPAA-compliant AI operations