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NavamAI

✓ verifiedFree

CLI-based personal AI that runs 15+ LLMs from your terminal and pairs with Markdown tools like Obsidian and VS Code.

991 visits/mo

Workik

✓ verifiedFreemium

AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.

210K visits/mo

Continue

✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

775K visits/mo

Cody

✓ verifiedPaid

Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.

245K visits/mo

Trae

✓ verifiedFreemium

Trae AI-powered IDE for developer collaboration; notable ByteDance-backed dev product.

2.3M visits/mo

Pricing

No public pricing

Trial: $0/month (20 AI requests on signup, 7 requests/day, 50 free flow runs, up to 3 users)

Starter: $15/month billed annually or $25/month (20M standard AI tokens, 1,000 flow runs)

Premium: $30/month billed annually or $50/month (40M standard + 4M advanced AI tokens, 3,000 flow runs)

Elite: $80/month billed annually or $150/month (100M standard + 10M advanced AI tokens, 10,000 flow runs)

Tailored: $62/month (custom AI token allocation)

Free trial available

No public pricing

Enterprise: starting at $16K (includes AI feature credits, scales with team size)

No public pricing

Core features

✦Terminal/CLI interface for prompting LLMs
✦Access to 15 models across 7 providers
✦Markdown workflow integration (Obsidian, VS Code, MkDocs)
✦Situational web-app generation and local run
✦Web scraping/content extraction (gather)
✦Vision-model support for images
✦Configurable prompt templates and intents

✦Automatic context-gathering from connected engineering sources
✦AI-generated code, tests and pull requests from tickets
✦Task planning that breaks complex work into subtasks
✦Auto-updating engineering documentation
✦Vector search over embedded project data
✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
✦Engineering productivity analytics dashboard

✦Open-source AI code assistant
✦Customizable autocomplete
✦In-editor AI chat
✦Community-built coding agent

✦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

✦AI Agents
✦Tool Integration
✦Context Awareness
✦Smart Autocompletion
✦Local Data Storage
✦Secure Data Access

Use cases

→Prompt and compare multiple LLMs from the terminal
→Generate and run small web apps without setup
→Automate Markdown document workflows
→Extract structured content from text and webpages

→Engineering teams automating ticket-to-PR workflows
→Developers wanting AI-assisted debugging and test generation
→Engineering managers tracking AI-driven productivity gains
→Teams centralizing documentation from scattered sources

→Get AI code completions while coding
→Ask questions about code in the editor
→Build on an open-source coding-agent foundation

→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

→Automating coding tasks with AI agents
→Integrating external tools for enhanced functionality
→Improving code accuracy with context-aware suggestions
→Boosting coding speed with smart autocompletion
→Building RAG apps without writing code

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