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Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
AI chat agent that investigates servers, clusters, databases, and Docker apps over SSH and proposes fixes for developers and SREs.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
No public pricing
No public pricing
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
- ✦Direct SSH, Kubernetes, and database connections without an installed agent
- ✦Bring-your-own-AI support for 14 providers including local models
- ✦Read-only or approval-gated command execution
- ✦Combined terminal and chat activity log
- ✦Project grouping for related infrastructure
- ✦Monitoring rules with plain-language alerting
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦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
- →Diagnosing production incidents from a phone away from a desk
- →Investigating server health without juggling SSH, dashboards, and log tools separately
- →Running approved database queries and fixes through an AI assistant
- →DevOps teams standardizing incident response across a fleet of servers
- →Engineers wanting local-model AI operations without exposing keys to a vendor backend
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
