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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
Agentic QA platform that drives a real browser or live API to verify AI-generated code and hands agents a fixable bug report.
Automatic AI CAPTCHA solver for reCAPTCHA and Cloudflare; high traffic but bypass niche.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
No public pricing
No public pricing
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦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
- ✦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
- ✦Automatic CAPTCHA solving
- ✦AI-powered automation
- ✦Image to text conversion
- ✦Browser extensions for CAPTCHA solving
- ✦Multi-language support
- ✦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
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →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
- →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
- →Web testing
- →Social media automation
- →Data collection
- →Market research
- →SEO optimization
- →Online shopping automation
- →Online gaming
- →Financial services automation
- →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