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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.
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Gumloop
✓ verifiedFreemium
No-code platform for building and running AI agents that automate work across data, sales and support tasks.
701K visits/mo
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Refraction.dev
✓ verifiedFreemium
AI coding assistant for editors and IDEs that explains, refactors, documents, and generates code across 56 languages.
2.8K visits/mo
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Sherloq
✓ verifiedFreemium
AI chat assistant for analysts that generates and fixes SQL using an organization's own saved query history.
12K visits/mo
Pricing
No public pricing
Pro: $37/month (20k+ credits/month, unlimited seats)
Hobby: Free (10 code generations, 1 user)
Pro: $8/mo (unlimited generations, editor extensions)
Team: $14/user/mo (multiple members, shared history)
Free trial available
No public pricing
No public pricing
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦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
- ✦Bug detection and fix suggestions
- ✦Code and CSS framework conversion
- ✦Unit test and documentation generation
- ✦Regex, SQL query, and CI/CD pipeline generation
- ✦Code explanation and style checking
- ✦Editor extensions for VS Code, Sublime, JetBrains, Visual Studio
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- ✦AI chat trained on the user's own SQL repository
- ✦query saving, tagging, and versioning
- ✦team folder permissions and sharing
- ✦Chrome extension and IntelliJ plugin
- ✦SOC2-compliant security with no database access needed
- ✦table and field lookup assistance
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →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
- →Generating unit tests for existing functions
- →Refactoring legacy code to modern practices
- →Producing inline documentation automatically
- →Learning new programming languages or concepts via AI explanations
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- →sharing reusable SQL snippets across an analytics team
- →quickly fixing syntax errors in existing queries
- →onboarding new analysts to a team's existing SQL logic
- →building a searchable personal or team SQL knowledge base
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