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Lapu AI

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Paid
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Lapu AI is a desktop AI agent for macOS and Windows that utilizes advanced language models to organize and perform multi-step processes directly on your computer. It accesses local files, executes terminal commands, and coordinates actions across applications like Google Workspace, Notion, GitHub, and Figma while ensuring permission-based, privacy-focused operations. By transforming plain-language objectives into approved, repeatable automations, it manages repetitive tasks like document processing, data extraction, file management, and cross-application workflows, delivering outcomes instead of merely answers.

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Paid
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Adapt is a universal AI work agent that integrates with your company's tools and data within Slack. It answers questions using live business context, automates complex workflows, and enables code-free app creation. Its AI retrieves relevant context, directs queries to optimal models for data analysis, and performs actions across systems, providing teams with evidence-based answers, reducing manual tasks, and speeding up decision-making.
Paid
Upvote 0
Lapu AI is a desktop AI agent for macOS and Windows that utilizes advanced language models to organize and perform multi-step processes directly on your computer. It accesses local files, executes terminal commands, and coordinates actions across applications like Google Workspace, Notion, GitHub, and Figma while ensuring permission-based, privacy-focused operations. By transforming plain-language objectives into approved, repeatable automations, it manages repetitive tasks like document processing, data extraction, file management, and cross-application workflows, delivering outcomes instead of merely answers.
Paid
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Twin is a no-code AI agent platform that transforms plain-English instructions into autonomous automations, connecting to APIs, controlling browsers, and executing workflows. It uses AI to design steps, manage exceptions, adapt to site changes, and select optimal models, enabling non-technical teams and enterprises to automate repetitive tasks, reduce costs, and achieve production-ready outcomes without coding.