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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.

Augment Code logo
Augment Code
✓ verifiedPaid

Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.

544K visits/mo
Numa logo
Numa
✓ verifiedPaid

AI operating system for car dealerships with voice AI, a smart inbox and agents that capture leads and lift service revenue.

207K visits/mo337 saves
PromptLayer logo
PromptLayer
✓ verifiedFree

Prompt engineering, management, and LLM observability platform.

212K visits/mo
Convex logo
Convex
✓ verifiedFreemium

TypeScript backend-as-a-service with a reactive database, server functions, auth and file storage for full-stack and AI apps.

692K visits/mo20K saves
Pricing
Business: $100/mo flat (up to 50 seats, $100 usage included)

Free trial available

No public pricing

No public pricing

Free & Starter: $0/mo (pay-as-you-go, 1-6 developers)
Professional: $25/developer/mo
Business & Enterprise: $2,500/mo minimum
Core features
  • Context Engine for codebase understanding
  • Agents across the full SDLC
  • Model routing / bring-your-own-keys
  • Automated code review and test coverage
  • CLI, MCP and native tool integrations
  • Enterprise security (SOC 2, ISO 42001, SSO)
  • Voice AI with full customer context
  • AI-native Smart Inbox across channels
  • LiveCSI real-time satisfaction monitoring
  • Service Advisor Agent
  • Heat Case and Opportunity Agents
  • Mobile app
  • Prompt management
  • Prompt evaluations
  • LLM observability
  • Team collaboration
  • Version control for prompts
  • A/B testing of prompts
  • Prompt Registry
  • Historical backtests
  • Regression tests
  • Usage monitoring
  • Reactive real-time database
  • TypeScript server functions (queries/mutations/actions)
  • Built-in authentication
  • Cron jobs and backend workflows
  • File storage, text and vector search
  • ACID transactions; open-source/self-host
Use cases
  • Automating PR code review
  • Raising test coverage
  • Incident investigation and remediation
  • Large-scale migrations and onboarding
  • Answering dealership calls and messages
  • Rescuing and booking service leads
  • Resolving customer complaints (heat cases)
  • Boosting service-advisor productivity
  • Scaling customer support automation with LLMs
  • Empowering non-technical teams with prompt engineering
  • Building personalized AI interactions
  • Debugging LLM agents
  • Improving content creation processes
  • Managing and monitoring prompts with a team
  • Building real-time reactive apps
  • Backends for AI agents
  • Replacing Firebase or Supabase
  • Full-stack TypeScript development
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