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The New GitBook
✓ verifiedFreemium
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
👁 653K/mo♥ 2.9K
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QuickFiling
✓ verifiedFreemium
AI-guided immigration petition drafting for NIW, EB-1A, EB-1B, O-1, I-485, and EB-5 cases, priced per case type.
👁 17K/mo
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Code Autopilot
✓ verifiedFreemium
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Pricing
No public pricing
Free trial available
No public pricing
No public pricing
Dr. I-485: $299 (free to start)
Dr. Visa: $199 (free to start)
Dr. NIW: $749 (free to start)
Dr. EB1A: $949 (free to start)
Dr. EB1B: $949 (free to start)
Dr. O-1: $949 (free to start)
Dr. EB-5: $999 (free to start)
No public pricing
Core features
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦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)
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- ✦Category-specific AI specialists for NIW, EB-1A, EB-1B, O-1, I-485, and EB-5
- ✦Free initial eligibility evaluation before payment
- ✦Automated organization of supporting evidence and exhibits
- ✦Drafts full USCIS-ready petition letters and document checklists
- ✦Optional RFE (Request for Evidence) response drafting
- ✦DS-160 prep and consular interview guidance for nonimmigrant visas
- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
Use cases
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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- →Self-filing petitioners building an NIW or EB-1A case without full attorney drafting
- →Immigration attorneys speeding up evidence organization and drafting
- →Employers preparing EB-1B outstanding researcher petitions
- →Visa applicants preparing DS-160 answers and interview readiness
- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
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