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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
Google Antigravity logo
Google Antigravity
✓ verifiedFree

Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.

22M visits/mo18K saves
Openlayer logo
Openlayer
✓ verifiedFreemium

AI governance and observability platform with 100+ automated tests and real-time guardrails to evaluate and monitor ML/LLM systems.

24K visits/mo
27K visits/mo
Agenta logo
Agenta
✓ verifiedFreemium

Open-source LLMOps platform uniting prompt management, evaluation and observability for teams shipping reliable LLM apps.

34K visits/mo
Pricing
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)

No public pricing

Basic: Free (20k inferences/mo, 1 member, 5 projects)

No public pricing

No public pricing

Core features
  • 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
  • Agent-first IDE experience
  • Autonomous planning and code execution
  • Integrated editor, terminal and browser control
  • Powered by Google's Gemini models
  • High-level developer supervision
  • 100+ automated AI tests
  • Offline evaluation and CI/CD for AI
  • Real-time observability and tracing
  • Guardrails against PII leaks, injection, hallucination
  • Data-quality and drift monitoring
  • Compliance/governance alignment
  • Git, SDK, CLI and REST API integration
  • Open-Source AI Gateway
  • Multi-LLM Management & Cost Optimization
  • Efficient and Secure LLMs Invocation
  • Unified API Signature for LLMs
  • Load Balancer for seamless switching between LLMs
  • Fine-Grained Traffic Control for LLMs
  • LLM Quota Management
  • Real-time LLM Traffic Monitoring
  • Caching Strategies for AI in Production
  • Flexible Prompt Management
  • Prompt management as a single source of truth
  • Playground for prompt experimentation
  • Evaluation to measure changes before production
  • Observability and tracing for debugging
  • Collaboration across technical and non-technical roles
  • Open-source and self-hostable
Use cases
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
  • Building apps with AI agents
  • Automating multi-step coding tasks
  • Prototyping and iterating on software
  • Assisting developers on complex work
  • Evaluate models before production
  • Monitor live AI systems for issues
  • Prevent unsafe or non-compliant outputs
  • Catch data drift and quality problems
  • Building API portals for secure sharing of internal APIs with partners.
  • Tracking API usage and driving API monetization.
  • Managing and securing API access in compliance with enterprise policies.
  • Connecting to multiple AI large models simultaneously.
  • Optimizing LLM costs and improving efficiency.
  • Protecting against LLM attacks and data leaks.
  • Version and manage prompts centrally
  • Benchmark and evaluate LLM outputs
  • Debug and trace production LLM issues
  • Collaborate across a team on LLM apps
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