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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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BasicAI Cloud
✓ verifiedFreemium
Data-annotation platform with AI-assisted labeling tools and team workflows for building ML training datasets.
👁 22K/mo
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Lovable
✓ verifiedFreemium
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
👁 35M/mo♥ 69K
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Pipedream
✓ verifiedFreemium
Low-code integration platform for connecting thousands of APIs into workflows and AI agents, including an MCP tool server.
👁 498K/mo
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
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)
- ✦AI-assisted data annotation tools
- ✦Training-data platform (BasicAI Cloud)
- ✦Team and project management
- ✦Annotation services
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Visual and code-based workflow builder
- ✦Prebuilt AI agent builder and deployment
- ✦Managed authentication across thousands of apps
- ✦MCP server exposing integrations as agent tools
- ✦Scheduled and event-triggered workflows
- ✦Connect SDK for embedding integrations into other products
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
- →Labeling images and data for ML models
- →Managing annotation teams and projects
- →Producing training datasets at scale
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Building AI agents that call external APIs and tools
- →Automating cross-app workflows such as Slack, Gmail, or Sheets notifications
- →Embedding third-party integrations into a SaaS product
- →Prototyping event-driven automations without heavy infrastructure
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