Intel Distribution of OpenVINO Toolkit
Accelerate deep learning inference across Intel hardware for edge and cloud deployment.

Your own, personal intelligence. An AI Assistant that adapts to how you work, acts before you ask, and is entirely yours to customize.
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Vellum is a sophisticated desktop AI assistant designed for macOS, focusing on deep personal integration and proactive task automation. It operates locally on your machine, leveraging advanced AI models like Gemini 3, GPT-5.5, and Claude Opus 4.7 to understand context, connect diverse tools, and execute actions on your behalf. Its core technical stack prioritizes user privacy and security, storing credentials in macOS Keychain and ensuring all data remains on your device, with messages sent to cloud AI models for responses never used for training. Vellum distinguishes itself with a 'time-to-intuition' learning rate, rapidly adapting to user preferences and workflows. It features a robust trust and permissions system (v3 rules engine) that requires explicit user approval for actions, offering granular control over its capabilities, including direct computer interaction via macOS accessibility and screen recording. Vellum automates routine tasks across various applications like Gmail, GitHub, Slack, and Linear, streamlining workflows from email triage to project backlog management.
Vellum is a sophisticated desktop AI assistant designed for macOS, focusing on deep personal integration and proactive task automation.
Explore all tools that specialize in email reading, drafting, and prioritization. This domain focus ensures Vellum delivers optimized results for this specific requirement.
Explore all tools that specialize in github issue triaging, labeling, and assignment. This domain focus ensures Vellum delivers optimized results for this specific requirement.
Explore all tools that specialize in slack channel monitoring, summarization, and conversation management. This domain focus ensures Vellum delivers optimized results for this specific requirement.
Explore all tools that specialize in linear board creation, updating, and reprioritization. This domain focus ensures Vellum delivers optimized results for this specific requirement.
Explore all tools that specialize in local computer interaction (file editing, desktop cleanup). This domain focus ensures Vellum delivers optimized results for this specific requirement.
Explore all tools that specialize in document writing and management. This domain focus ensures Vellum delivers optimized results for this specific requirement.
Open side-by-side comparison first, then move to deeper alternatives guidance.
Vellum runs locally on macOS, ensuring user data, memories, and credentials are stored on the machine. Messages are sent to cloud AI model providers (like Anthropic, OpenAI) for response generation but are explicitly not used for training. Credentials reside in the macOS Keychain and are executed by a deterministic service, never directly by the AI, maintaining a strong isolation layer.
Vellum integrates natively with critical productivity tools (Gmail, GitHub, Slack, Linear) to perform proactive, multi-step automations. It boasts a '72h time-to-intuition rate,' indicating rapid learning and adaptation to user workflows, anticipating needs and acting before explicit requests. This is underpinned by a v3 rules engine for complex decision-making and permissions management.
With user permission, Vellum can see the computer screen and interact with UI elements via macOS accessibility and screen recording permissions. Actions are governed by an explicit permission system (once, per thread, within a time-frame, always, or never), enforced by traditional software mechanisms, not the AI itself.
Manually sifting through a large volume of emails, drafting routine replies, and prioritizing important messages consumes significant time and mental effort.
Vellum autonomously reads, drafts, and prioritizes incoming emails based on user preferences.
It clears newsletters, receipts, and notifications by archiving them.
Drafts replies for common inquiries, ready for user review.
Marks important emails for immediate user attention.
User opens Gmail to a clean inbox, with decisions ready, not a wall of unread messages.
Triaging, labeling, assigning, and responding to GitHub issues manually can be time-consuming and lead to delays in issue resolution.
Vellum monitors GitHub repositories for new issues.
Based on team rules and issue content, it automatically applies labels (e.g., 'bug', 'auth', 'P1').
It assigns issues to the relevant team members or roles (e.g., '@engineer').
Vellum can draft initial responses or provide context from related PRs/issues, accelerating the triage process before human intervention.
Project backlogs often become stale or inaccurate because manual updates after every meeting, discussion, or incident are impractical and time-consuming.
Vellum joins relevant Slack channels (e.g., #engineering) to monitor conversations.
When critical information, blockers, or new tasks emerge from discussions (e.g., a bug report in Slack), Vellum identifies them.
It automatically creates new issues in Linear, populating them with relevant details from the Slack thread.
Labels (e.g., 'bug', 'auth', 'P1') and assignments are applied, ensuring the Linear board accurately reflects current priorities and assignments derived from real-time communication.
Verified feedback from other users.
Choose the right tool for your workflow
Vellum offers deep local integration and proactive automation on your device, unlike ChatGPT or Claude, which are primarily cloud-based conversational interfaces. Vellum learns and acts on your behalf across applications, prioritizing data privacy by keeping your data on your machine.
While OpenClaw is a powerful open-source agent for developers, Vellum is designed for broader accessibility with a native macOS app, guided onboarding, and a more structured permission system. Vellum prioritizes user trust and explicit approvals, offering more guardrails compared to OpenClaw's full autonomy.
Vellum offers a more personalized, local-first AI assistant experience with deep integration into the macOS environment and user applications beyond the Microsoft ecosystem. It focuses on highly customized, proactive automation and strong data privacy by keeping user data on the device, whereas Copilot is more integrated with Microsoft 365 services and relies on cloud processing.
Accelerate deep learning inference across Intel hardware for edge and cloud deployment.

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