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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.
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Cody
✓ verifiedPaid
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
245K visits/mo
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Sherpa Coder
✓ verifiedFree
VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
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LightOn
✓ verifiedFreemium
Production RAG API for developers: parse, extract and search documents with SOTA OCR and cited retrieval, cloud or on-prem.
29K visits/mo
Pricing
No public pricing
Enterprise: starting at $16K (includes AI feature credits, scales with team size)
No public pricing
Free: $0
Basic: $16 per month
Pro: $90 per month
Ultra: $299 per month
Starter: Free + usage (parsing €0.002/page)
Business: €149/mo + usage (100 GB storage, unlimited users)
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)
- ✦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
- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦Custom AI chatbot creation
- ✦Data-driven training (URLs, PDFs, CSVs, Q&A)
- ✦Multi-language support (90+ languages)
- ✦Integration with CRMs, APIs, and tools like Zapier & Google Drive
- ✦Human handoff feature
- ✦Actions & Automation
- ✦Parse endpoint with SOTA OCR (LightOnOCR-2)
- ✦Extract endpoint for schema-based JSON
- ✦Search endpoint with hybrid retrieval and citations
- ✦MCP-native and LLM-agnostic
- ✦Workspaces and chunk-level access control
- ✦On-prem, VPC or air-gapped deployment
Use cases
- →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
- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →Lead generation and qualification
- →E-commerce sales assistance
- →Healthcare patient support
- →SaaS customer service
- →Banking assistance
- →Retail personalized shopping
- →Hospitality concierge services
- →Build production RAG without a long in-house pipeline
- →OCR and structure scanned documents
- →Grounded document search with citations for agents
- →Deploy secure enterprise document intelligence
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