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LLM Evaluation Coding Agents Foundation Model Providers LLM Ops Observability Llms Foundation Models AI Agents AI Agents Infrastructure

LangWatch

✓ verifiedFreemium

Platform to test, evaluate and observe LLM and voice AI agents, with prompt management and red-teaming for production.

23K visits/mo6.4K saves

liteLLM

✓ verifiedFreemium

Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.

703K visits/mo

Claude

✓ verifiedFreemium

Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.

22M visits/mo231K saves

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

Pricing

Developer: €0 (50k events/mo)

Growth: €29/core-seat/mo (+ €5 per 100k events)

Open Source: $0 (self-hosted, 100+ providers)

Free trial available

Free: $0

Pro: $17/month billed annually ($200 up front), or $20/month

Max: From $100/month

Team: $20/seat/month billed annually ($25 monthly); premium seats $100/seat/month annually ($125 monthly)

Enterprise: Contact 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)

Core features

✦Scenario-based agent testing
✦LLM evaluation and quality scoring
✦Observability for cost and latency
✦Prompt management with GitHub sync
✦Voice AI simulation
✦LLM red-teaming and governance

✦Unified access to 100+ LLMs in OpenAI format
✦Cost/spend tracking per key, user and team
✦Budgets and rate limiting
✦Automatic provider fallbacks and retries
✦Virtual keys and team management
✦Logging and observability integrations

✦Conversational writing and editing
✦Code generation and debugging (Claude Code)
✦Data analysis and visualization
✦Web search plus memory across chats
✦Connectors and remote MCP integrations
✦Extended thinking for complex tasks

✦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

Use cases

→Catch agent issues before production
→Evaluate and monitor LLM quality
→Test voice AI agents at scale

→Giving developers governed access to many LLMs
→Attributing and controlling LLM spend
→Keeping apps running during provider outages

→Drafting and refining written content
→Building and debugging software
→Analyzing datasets for insights
→Research and learning support
→Team and enterprise automation

→Turning prompts into maintainable, spec-matched code
→Catching bugs unit tests miss
→Reviewing PRs and fixing bugs in CI/CD

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