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Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
Headless, open-source rich-text editor framework with paid add-ons for collaboration, comments, AI editing agents and document conversion.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
No public pricing
Free trial available
Free trial available
Free trial available
- ✦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
- ✦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
- ✦Headless, extensible core editor with 100+ extensions
- ✦Real-time collaborative editing with live cursors
- ✦Inline and document comments
- ✦DOCX, ODT and Markdown import/export
- ✦AI Toolkit for building document-editing AI agents
- ✦Prebuilt UI components and editor templates
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- →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
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms
- →Building a custom rich-text editor for a SaaS product
- →Adding real-time collaboration to a document app
- →Letting an AI agent edit documents with tracked changes
- →Importing or exporting Word or Markdown content in-app
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
