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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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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

👁 775K/mo

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K
Gumloop
✓ verifiedFreemium

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

👁 701K/mo
GitFluence
✓ verifiedFree

Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.

Ai2sql
✓ verifiedFreemium

Text-to-SQL tool that writes dialect-aware queries and gives AI agents governed, read-only database access.

9.0K
Pricing

No public pricing

No public pricing

Pro: $37/month (20k+ credits/month, unlimited seats)

No public pricing

Start: $5/mo
Pro: $11/mo (unlimited queries)
Team: $23/mo (5 users)

Free trial available

Core features
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • 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
  • Natural-language to Git command suggestions
  • AI-driven command matching
  • Copy-ready command output
  • Git guides and reference
  • Natural-language to SQL
  • Semantic schema layer
  • Governed MCP/REST gateway
  • Read-only query enforcement
  • 7 database connectors
  • SQL explain, optimize and format
Use cases
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • 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
  • Find the correct Git command quickly
  • Learn Git syntax by describing a goal
  • Avoid memorizing Git flags
  • Generating SQL without coding
  • Giving agents safe DB access
  • Explaining and fixing queries
  • Querying live databases
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