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Credit-based AI coding agent that builds full applications from plain-language instructions, including backend, billing, and admin features.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.
Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.
Free trial available
No public pricing
No public pricing
No public pricing
- ✦Builds complete apps (auth, storage, payments, admin) from natural-language prompts
- ✦Runs on top of multiple frontier coding models
- ✦Retains full project context across sessions for incremental feature additions
- ✦Remote task submission via Slack/Telegram messaging
- ✦'Eco Mode' for lower-cost usage without consuming credits
- ✦VS Code and JetBrains IDE integrations plus a desktop app
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- ✦Conversational writing and editing
- ✦Code generation and debugging (Claude Code)
- ✦Data analysis and visualization
- ✦Web search plus memory across chats
- ✦Connectors and remote MCP integrations
- ✦Extended thinking for complex tasks
- ✦Dialogue with GLM large model
- ✦AI search
- ✦AI drawing
- ✦AI reading
- ✦AI-generated video (沉思清影-AI生视频)
- ✦AI-generated PPT
- ✦Data analysis tools
- ✦Code assistance (代码速写)
- ✦Intelligent agents
- →Solo founders building a launchable product without a dev team
- →Developers offloading multi-step feature builds to an autonomous agent
- →Teams wanting a shared coding agent with pooled usage billing
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →Drafting and refining written content
- →Building and debugging software
- →Analyzing datasets for insights
- →Research and learning support
- →Team and enterprise automation
- →Engaging in conversations with an AI model
- →Generating images and videos using AI
- →Creating presentations with AI assistance
- →Analyzing data with AI tools
- →Assisting with code development