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Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
Developer API suite (Reader, Embeddings, Reranker) that turns web content into LLM-ready data for search and RAG.
Infrastructure company building large-scale GPU data centers and compute for AI, including Anthropic's compute buildout.
Creative AI infrastructure giving studios access to 500+ image, video, 3D, and audio models plus custom brand-trained models.
AI cloud offering model APIs, GPU instances, and serverless GPUs; high traffic.
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦Reader API converts URLs to Markdown
- ✦Multimodal multilingual embedding models
- ✦Reranker for stronger search relevance
- ✦Web search endpoint returning SERP data
- ✦MCP server for use inside LLMs
- ✦Native inference inside Elasticsearch
- ✦Large-scale GPU and data-center infrastructure for AI
- ✦Power acquisition and data-center design/build
- ✦Fast deployment (gigawatts in ~6 months)
- ✦Operates both hardware and software stack
- ✦Custom LoRA model training from 5-100 reference images
- ✦Access to 500+ models across 50+ providers
- ✦Visual workflow builder for multi-step generation pipelines
- ✦API-first and MCP-ready for agent integration
- ✦Batch generation at scale with reusable templates
- ✦One-click shareable apps built from workflows
- ✦SOC 2 Type II compliance and SSO
- ✦Model APIs
- ✦GPU Instances
- ✦Serverless GPUs
- ✦Custom Model Deployment
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →Ground LLMs with clean web content
- →Build semantic and RAG search
- →Rerank retrieved results
- →Give AI agents live web access
- →Training and running large AI models at scale
- →Provisioning GPU compute for AI labs
- →Building dedicated AI data-center capacity
- →Generating on-brand creative assets at scale
- →Building custom AI-powered creative workflows and apps
- →Comparing outputs across many AI models in one workspace
- →Automating batch content production for teams
- →Deploy AI models for various applications using a simple API.
- →Scale AI applications with serverless GPUs.
- →Access high-performance GPUs for demanding workloads.
- →Deploy custom models with guaranteed performance and scalability.