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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.

TinyCommand
✓ verifiedFreemium

All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.

👁 31K/mo

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

5.2K
Cody
✓ verifiedPaid

Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.

👁 245K/mo
Modal
✓ verifiedFreemium

Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.

👁 988K/mo
Pricing
Free: $0/mo (1,000 credits, 1 seat, unlimited forms)
Basic: $17/mo billed annually at $199/yr (10,000 credits, 3 seats)
Professional: $42/mo billed annually at $499/yr (50,000 credits, 10 seats)
Agency: $125/mo billed annually at $1,499/yr (250,000 credits, 50 seats)

No public pricing

Enterprise: starting at $16K (includes AI feature credits, scales with team size)
Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
Core features
  • Drag-and-drop form builder with conditional logic
  • Workflow automation with 60+ node types and 400+ integrations
  • Prebuilt and custom AI agents for tasks like lead scoring
  • Relational database with AI-enriched columns
  • Drag-and-drop email builder with AI-drafted content
  • Company and contact enrichment and web research tools
  • 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)
  • Codebase-aware developer chat
  • AI code completions and inline edits
  • Customizable and shareable prompts
  • Automatic bug identification and debugging help
  • Context filters to exclude sensitive repos
  • Integrates with major code hosts and IDEs
  • Serverless GPU compute defined in Python
  • Sub-second container cold starts
  • Autoscale 0 to 1000+ GPUs
  • Inference, training and batch workloads
  • Secure sandboxes for untrusted code
  • Built-in logging and observability
Use cases
  • Capturing and automatically routing sales leads
  • Building onboarding or support-triage workflows
  • Running AI-driven lead scoring and qualification
  • Sending personalized, data-merged email campaigns
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Engineers asking questions about an unfamiliar large codebase
  • Teams standardizing common coding tasks with shared prompts
  • Developers debugging errors faster with AI-assisted context
  • Enterprises running large-scale code migrations
  • Deploying and scaling model inference
  • Fine-tuning and training models
  • Running batch/parallel AI jobs
  • Executing untrusted code in sandboxes
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