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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.

Helicone logo
Helicone
✓ verifiedFreemium

LLM observability platform and AI gateway that lets teams route, log, debug and analyze their model requests.

100K visits/mo
Higress logo
Higress
✓ verifiedFreemium

Open-source AI-native API gateway for routing, protecting and caching LLM/agent traffic, with a paid managed cloud.

29K visits/mo
hCaptcha logo
hCaptcha
✓ verifiedFreemium

Privacy-focused CAPTCHA and bot/fraud-detection service, a drop-in reCAPTCHA alternative for websites and apps.

4.4M visits/mo
Coze logo
Coze
✓ verifiedFreemium

ByteDance's Coze (Kouzi): an all-in-one AI office assistant for writing, slides, sheets, design, podcasts and images.

7.2M visits/mo
Pricing
Hobby: Free (10,000 requests/mo)
Pro: $79/mo (unlimited seats)
Team: $799/mo (SOC-2 & HIPAA)

Free trial available

No public pricing

Basic: Free
Pro: $139/month billed monthly, $99/month billed yearly
Enterprise: Contact sales

Free trial available

No public pricing

Core features
  • Request logging and LLM observability
  • AI gateway with routing and automatic fallbacks
  • Caching and rate limiting
  • Session, user and custom-property analytics
  • Prompts, playground and datasets for testing
  • Integrations with OpenAI, Anthropic, Azure and more
  • Unified proxy and protocol conversion across 100+ LLMs
  • Model-level fallback and routing
  • Semantic and exact-match AI caching
  • Token tracking and quota controls
  • Content-safety and data-protection filtering
  • MCP service hosting and plugin marketplace
  • AI bot detection
  • Transaction fraud protection
  • Account-takeover (ATO) defense
  • Pull-based SMS MFA
  • Private Learning ML risk models
  • Two-line reCAPTCHA migration
  • Hundreds of integrations
  • AI writing
  • AI presentation/PPT generation
  • AI spreadsheets and tables
  • AI design
  • AI podcast generation
  • AI image generation
Use cases
  • Monitoring and debugging LLM apps
  • Analyzing model usage and cost
  • Caching responses to cut spend
  • Managing prompts and testing datasets
  • Centralizing access to multiple LLM providers
  • Building and governing AI agent/MCP services
  • Controlling token spend across teams
  • Adding caching and safety to LLM calls
  • Blocking bots and spam signups
  • Preventing account takeover
  • Reducing transaction and payment fraud
  • Stopping credential stuffing
  • Drafting documents
  • Building presentations
  • Generating spreadsheets
  • Creating designs and images
  • Producing podcasts
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