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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.

Frontegg logo
Frontegg
✓ verifiedFreemium

Low-code customer identity and access management (CIAM) platform handling authentication and user management for SaaS apps.

9.0K saves
exa.ai logo
exa.ai
✓ verifiedFreemium

Search, crawling and research API built for AI agents, with token-efficient results and structured web-data enrichment.

761K visits/mo1.7K saves
BlackBox AI logo
BlackBox AI
✓ verifiedFreemium

AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.

3.9M visits/mo
Supernova.io logo
Supernova.io
✓ verifiedFreemium

Design-system platform that packages tokens, code components, and rules into scoped context for AI coding agents.

93K visits/mo
Pricing

No public pricing

Free: $0 (20,000 requests/mo)
Search: $7/1k requests
Contents: $1/1k pages
Deep Search: $12-15/1k requests
Monitors: $15/1k requests
Agent: $0.012-$1.00/run
Pro: $10/mo
Pro Plus: $20/mo
Pro Max: $40/mo
Pro: $35/mo per full seat (up to 15 seats, billed monthly)
Core features
  • Low-code CIAM identity layer
  • Authentication and authorization for SaaS apps
  • Self-service user and org management
  • Security across all product entry points
  • Agentic AI access layer (Agen.co)
  • Web search API tuned for agents
  • Full-page contents with token-efficient highlights
  • Asynchronous agents for deep research and enrichment
  • Structured outputs with grounded citations
  • Web monitors that track new events on a schedule
  • Zero data retention and SOC 2 Type II controls
  • Unified encrypted inference endpoint
  • Multi-agent parallel execution
  • CLI, IDE, and API access
  • App builder and remote coding agents
  • Chairman LLM output evaluation
  • 35+ IDE integrations
  • Scoped MCP context distribution to multiple AI coding tools
  • Design token and component API management
  • Collaborative documentation with analytics
  • Figma and Storybook data source integration
  • Feedback loop for improving AI context quality
  • Skill and exporter management for agent capabilities
Use cases
  • Adding login and auth to a SaaS product
  • Managing customer users and organizations at scale
  • Securing multiple product entry points
  • Exposing a product safely to AI agents
  • Give coding agents current docs and repo context
  • Power chatbots with real-time web answers
  • Enrich company and people data at scale
  • Monitor the web for fresh events
  • Automating refactors, tests, and migrations
  • Running competing AI coding agents
  • Building apps from prompts
  • Integrating agents into CI/CD
  • Product teams giving AI coding agents accurate design-system context
  • Design system managers publishing a single source of truth
  • Engineering teams reducing token usage by scoping agent context per team
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