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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
Gumloop logo
Gumloop
✓ verifiedFreemium

No-code platform for building and running AI agents that automate work across data, sales and support tasks.

701K visits/mo
16x Prompt logo
16x Prompt
✓ verifiedFreemium

Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.

21K visits/mo
Pricing
Business: $100/mo flat (up to 50 seats, $100 usage included)

Free trial available

Pro: $37/month (20k+ credits/month, unlimited seats)
Free: $0 (10 prompts/day)
Individual lifetime license: $48
Team lifetime license: $68
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)
  • Visual canvas to orchestrate multi-agent workflows
  • Prebuilt specialized agents (data, support, CRM, sales)
  • Access to many AI models with no vendor lock-in
  • Slack, Teams and email agent interaction
  • Recurring/scheduled tasks and triggers
  • Enterprise security: RBAC, VPC, audit logs, spend controls
  • Source-code context and prompt management
  • Custom and formatting instructions
  • BYOK API integrations (OpenAI, Claude, Gemini, etc.)
  • Token-limit tracking
  • Code-edit feature with visual diffs and backups
  • Local, offline prompt generation
Use cases
  • Automating PR code review
  • Raising test coverage
  • Incident investigation and remediation
  • Large-scale migrations and onboarding
  • Automate data analysis and reporting
  • Triage support tickets and spot patterns
  • Keep a CRM updated and research prospects
  • Deploy AI agents across a team's tools
  • Building context-rich prompts for AI coding
  • Comparing model outputs on the same task
  • Reusing saved prompts across tech stacks
  • Keeping code private during prompt creation
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