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Lovable
✓ verifiedFreemium
Chat-based AI builder turning ideas into full software products.
👁 35M/mo♥ 69K
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devActivity
✓ verifiedFreemium
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
👁 52K/mo
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Watsonx.data
✓ verifiedFree trial
IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.
Pricing
No public pricing
No public pricing
Free trial available
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
No public pricing
No public pricing
Free trial available
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)
- ✦AI-powered software development
- ✦Chat-based interface for specifying requirements
- ✦Full-stack engineering capabilities
- ✦Rapid app prototyping
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
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- ✦Open hybrid data lakehouse
- ✦Connects data across clouds and on-prem
- ✦Governance, lineage and access controls
- ✦Business-context enrichment
- ✦AI-ready data for analytics and models
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Creating developer portfolios
- →Building real estate listings applications
- →Developing file uploaders
- →Generating slide presentations
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
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- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data
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