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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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
MindStudio logo
MindStudio
✓ verifiedFreemium

No-code visual builder to create, deploy and orchestrate AI agents across 200+ models, for individuals to enterprise.

1.8M visits/mo
Dify.ai logo
Dify.ai
✓ verifiedFreemium

Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.

1.1M visits/mo
Fiddler AI logo
Fiddler AI
✓ verifiedFreemium

Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.

51K visits/mo
27K 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)
Free: $0 + usage (1 agent, 1,000 runs/mo)
Individual: $20/mo + usage (unlimited agents and runs)
Sandbox: Free (200 message credits)
Professional: $590/workspace/year
Team: $1,590/workspace/year
Free: $0 (real-time guardrails)
Developer: $0.002 per trace

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
  • No-code visual agent builder
  • 200+ AI models via service router
  • 100+ prebuilt templates
  • Agent skills, plugins and workflows
  • AI Media Workbench for video/image
  • Enterprise controls (SSO, permissions, self-host)
  • Visual workflow studio for agents
  • RAG knowledge pipelines
  • Agent runtime with tools and memory
  • Marketplace of models and plugins
  • Publish as app, API or MCP tool
  • Logging, analytics and monitoring
  • End-to-end agentic and ML observability
  • Real-time guardrails (hallucination, PII, jailbreak)
  • Continuous evaluations and custom judges
  • Root-cause analysis and decision lineage
  • AI governance, risk, and compliance controls
  • Flexible SaaS, VPC, or on-prem deployment
  • 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
Use cases
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
  • Automating business workflows
  • Building custom AI agents without code
  • Content and media generation
  • Deploying agents across a team or org
  • Building AI agents and chatbots
  • Creating RAG-based knowledge apps
  • Deploying LLM apps at enterprise scale
  • Monitoring production AI agents
  • Enforcing safety guardrails on LLM apps
  • Evaluating and debugging model behavior
  • Governance and compliance for enterprise AI
  • 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.
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