Vellum

What

Vellum is a personal AI assistant for macOS and iOS that runs primarily on the user’s device and is designed to take real actions across everyday tools and workflows. Instead of acting only as a chat interface, it is positioned as a desktop assistant that can help manage email, calendars, Slack, web browsing, food ordering, coding, app building, and other routine tasks through a single conversation.

The product appears aimed at general knowledge workers and consumers rather than only developers or technical operators. Its core workflow is conversational task delegation: users describe what they want done, Vellum accesses approved apps or interfaces, proposes or executes actions with permission, and improves over time by learning user preferences and retaining local memory.

Features

• Local-first assistant runtime: Vellum stores files, memory, conversations, and credentials on the user’s machine, which reduces reliance on vendor-hosted storage.
• Action-taking across common tasks: It can handle activities such as email cleanup, Slack summarization, restaurant booking, grocery ordering, coding, and app building from one conversational interface.
• Per-action approval controls: External actions such as file access, shell commands, and API calls require explicit user approval, adding oversight before execution.
• Scoped access permissions: Users can decide what data and tools the assistant can access, which helps limit exposure to only the systems needed for a task.
• Encrypted local credential vault: API keys, OAuth tokens, and passwords are stored in an encrypted vault on-device and scoped to specific domains and tools.
• Extensible skill model: Vellum includes 60+ built-in skills and supports custom skills, allowing users to broaden what the assistant can do over time.

Helpful Tips

• Evaluate task categories first: This type of assistant is most useful for repetitive, multi-step personal productivity work such as inbox cleanup, scheduling, and summarization rather than highly regulated or high-risk operations unless controls are carefully reviewed.
• Review the privacy trade-off carefully: Although Vellum states local data stays on-device, the page also says conversations are sent to a cloud AI model provider for response generation, so buyers should distinguish local storage from model-processing behavior.
• Plan permission boundaries early: Adoption will likely be smoother if users define which apps, files, and actions are in scope before enabling broad assistant access.
• Use approval workflows as a trust-building phase: Products in this category are best introduced with human review enabled for all actions until users understand reliability and edge cases.
• Check platform fit: The current supported platforms are macOS and iOS, with Windows and Linux described only as roadmap items.

OpenClaw Skills

Vellum’s own FAQ positions it as more guided and consumer-friendly than OpenClaw, with a native macOS app, onboarding, and approval-based action controls. In an OpenClaw ecosystem, Vellum would likely fit as a front-end personal execution layer for less technical users, while OpenClaw-style skills and agents could serve as the more customizable automation back end. That is a likely use case, not a confirmed native integration from the page.

A practical OpenClaw-oriented workflow could include agents that generate custom Vellum-compatible task plans for inbox triage, executive scheduling, Slack recap generation, lightweight app prototyping, or personal operations dashboards. For professions such as founders, operators, and independent professionals, that combination could shift work from manual coordination toward supervised delegation: Vellum handling approved day-to-day execution, and OpenClaw-style skills supplying deeper automation logic, domain-specific workflows, or developer-grade extensions where needed.