IntelliSheet AI
Turn spreadsheets into intelligent data engines with native LLM orchestration and automated formula generation.
The cross-platform AI teammate with long-term memory and context-aware screen intelligence.
MeetHarper represents the 2026 paradigm shift from cloud-locked chatbots to persistent desktop agents. Architecturally, it functions as a context-aware layer sitting atop macOS and Windows environments, utilizing accessibility APIs and OCR to understand user intent across any application. Unlike standard LLM interfaces, Harper features a 'Local Memory' engine that indexes user-specified files, emails, and browsing history to provide a hyper-personalized RAG (Retrieval-Augmented Generation) experience. In the 2026 market, MeetHarper positions itself as a privacy-first alternative to Microsoft Copilot and Apple Intelligence, offering modular LLM support (allowing users to toggle between OpenAI, Anthropic, and local Llama-based models). Its technical edge lies in its 'Active Context' monitoring—a proprietary system that tracks screen changes to provide proactive assistance, such as summarizing a Zoom transcript as it's being generated or suggesting email replies based on a Slack thread visible in another window. This orchestration of screen intelligence and personal data makes it a critical tool for knowledge workers requiring seamless cross-app automation.
Uses low-latency optical character recognition to read and interpret any text or UI element on the screen in real-time.
Turn spreadsheets into intelligent data engines with native LLM orchestration and automated formula generation.
The privacy-first browser AI assistant for seamless content synthesis and context-aware automation.
The permission-aware generative AI and search platform for enterprise knowledge.
A personal AI designed to be supportive, smart, and available anytime.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Indexes local documents into a FAISS-based vector store hosted locally on the user's machine.
Dynamic routing that selects the most cost-effective or highest-performing LLM based on task complexity.
Integrates Whisper v3 with a command parser to execute UI actions via voice.
Maintains a semantic history of the clipboard, allowing users to 'Paste as JSON' or 'Summarize Clipboard'.
Executes sensitive data processing in a local environment before sending anonymized prompts to the cloud.
Conditional logic based on screen events (e.g., 'If I open a JIRA ticket, fetch related code from GitHub').
Manually taking notes during a video call is distracting and leads to missed information.
Registry Updated:2/7/2026
Old enterprise software lacks API connectivity, making data extraction difficult.
Employees waste hours searching for internal documentation scattered across PDFs and emails.