Logical is a proactive AI copilot that understands on-screen context to surface relevant next actions automatically. It identifies actionable to-dos from communications and distills meetings into summaries and action items without requiring workflow changes. The platform also offers in-place writing refinement and centralized access to connected tools and knowledge bases.
Funding
Funding not disclosed
Founders
Product
Problem
Knowledge workers spend significant time manually tracking action items, summarizing meetings, and switching between disparate productivity tools, which fragments workflow and reduces efficiency. Existing solutions often require explicit integrations or manual prompts, limiting real‑time assistance and increasing cognitive load.
Solution
Logical provides a proactive, on‑device AI copilot that continuously monitors on‑screen context across applications to surface the most relevant next actions without any setup overhead. It automatically extracts actionable to‑dos from emails, chats, and threads, and generates concise meeting summaries with key moments and follow‑up items, all without requiring bots or workflow changes. Users can highlight any text to invoke in‑place writing refinement—tone, clarity, and grammar adjustments are applied with full awareness of the surrounding document. The platform also offers a searchable clipboard history, unified querying across connected services, and instant knowledge‑base retrieval, all powered by a local‑first architecture that keeps data on the user’s device and encrypts any cloud queries. Custom filters and instant hide controls give users granular privacy and visibility settings, ensuring the assistant operates only where and when they permit.
Target Audience
Primary users are knowledge workers such as product managers, analysts, consultants, and remote team members who rely heavily on email, chat, documents, and virtual meetings to coordinate tasks and decisions.
Features
- Real‑time on‑screen context detection across macOS applications, enabling proactive action suggestions without manual integration
- Automatic extraction of to‑dos from emails, chat messages, and threaded conversations using large‑language‑model inference
- Lumos Mode for continuous situational awareness, maintaining context as users switch tasks
- AI‑driven meeting summarization that produces key‑moment highlights and actionable items directly from audio or transcript inputs
- In‑place text refinement with tone, clarity, and grammar adjustments triggered by simple text selection
- Searchable clipboard history that indexes copied content for instant reuse across apps
- Unified query engine for connected tools and personal knowledge bases, delivering instant answers while writing or thinking
- Local‑first processing architecture with end‑to‑end encryption, zero data collection, and optional cloud LLM queries
- Customizable filters and instant hide functionality to control which applications or windows are monitored