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One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Agentic QA platform that drives a real browser or live API to verify AI-generated code and hands agents a fixable bug report.
AI co-pilot for technical diagrams and design docs, with diagram-as-code and integrations for engineering teams.
Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
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- ✦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
- ✦Live browser/API testing rather than mocked assertions
- ✦Auto-generated failure bundles with root-cause hypotheses
- ✦CLI and MCP/IDE integration for AI coding agents
- ✦Auto-healing tests when the UI drifts
- ✦Growing regression suite that persists across development phases
- ✦No-code web app with live preview and video replay for QA teams
- ✦AI-generated diagrams from prompts
- ✦Diagram-as-code editing
- ✦Markdown design docs
- ✦Eraserbot auto-updating codebase diagrams
- ✦Integrations: GitHub, Notion, Confluence, VS Code
- ✦Export to PNG/SVG/PDF/MD and MCP server
- ✦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
- ✦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
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Verifying AI coding-agent output before merging code
- →Catching regressions from unattended overnight coding runs
- →QA teams testing live apps without writing test scripts
- →Gating CI/CD releases on end-to-end pass rates
- →Create architecture and cloud diagrams fast
- →Write and maintain design docs
- →Keep codebase diagrams up to date
- →Embed live diagrams in Notion/Confluence
- →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
- →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