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OpenRouter logo
OpenRouter
✓ verifiedFreemium

Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.

17M visits/mo
Kiro AI logo
Kiro AI
✓ verifiedFreemium

Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.

3.8M visits/mo
Sourcery Sentinel logo
Sourcery Sentinel
✓ verifiedPaid

Sourcery's AI agent for automated production issue fixing and code quality; established dev-tools brand.

82K visits/mo1.5K saves
Pricing
Free: $0
Pay-as-you-go: Per-token, no subscription
Enterprise: Talk to sales
Free: $0/mo (50 credits)
Pro: $20/user/mo (1,000 credits)
Pro+: $40/user/mo (2,000 credits)
Pro Max: $100/user/mo (5,000 credits)
Power: $200/user/mo (10,000 credits)
Code Quality - Open Source: Free
Code Quality - Pro: $12 per seat / month
Code Quality - Team: $24 per seat / month
Code Quality - Enterprise: Talk to us
Production Issues - Free: Free
Production Issues - Resilience Plus: $200 per month
Production Issues - Enterprise Uptime: Talk to us
Core features
  • One unified, OpenAI-compatible API for 400+ models
  • Automatic provider failover for higher uptime
  • Edge routing for low latency
  • Custom data and provider policies
  • Pay-as-you-go credits usable across any model
  • Spec-driven development (requirements, design, tasks)
  • Parallel agents, local or cloud
  • Property-based and correctness testing
  • Works in IDE, CLI, web and mobile
  • Multiple models (Claude, open-weight, Auto)
  • Headless CLI for CI/CD
  • Context from tools like Figma and Terraform
  • AI investigation and diagnosis of Sentry issues
  • Automated code fixes for production issues
  • Slack integration for instant alerts
  • One-click Pull Request (PR) creation for fixes
  • Code review for private repositories
  • Pull request summary generation
  • Mermaid diagrams for code visualization
  • Line-by-line code reviews
  • Custom code review rules
  • Repository analytics
Use cases
  • Accessing many LLMs through one integration
  • Adding provider redundancy to AI apps
  • Comparing model price and performance
  • Powering agents and AI-native products
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
  • Fixing production bugs and errors faster
  • Increasing system uptime and reliability
  • Reducing support and debugging costs
  • Automating code quality checks and improvements
  • Streamlining code review processes
  • Identifying and triaging critical Sentry issues
  • Enhancing code security through automated scanning
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