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Ask Fellow

Your personal, on-demand AI Chief of Staff for meetings

2025-06-18

Product Introduction

  1. Ask Fellow is an AI-powered meeting assistant designed to enhance productivity by managing meeting-related tasks before, during, and after sessions. It integrates deep meeting memory, automated execution of action items, and transparent reasoning to streamline decision-making and reduce reliance on additional meetings.
  2. The core value of Ask Fellow lies in its ability to act as a strategic partner, ensuring clarity, accountability, and efficiency across the entire meeting lifecycle. It eliminates redundant meetings by synthesizing insights, automating follow-ups, and maintaining a searchable repository of meeting outcomes.

Main Features

  1. Ask Fellow enables cross-meeting search functionality, allowing users to query decisions, action items, or bottlenecks across all historical meetings, including those they did not attend. This feature uses natural language processing to parse transcripts and recordings, delivering instant answers to questions like "What decisions were made last week?" or "What risks exist for Project X?"
  2. The tool automates the creation of deliverables such as performance reviews, board reports, or project summaries by extracting insights from meeting data. Users input a prompt, and Ask Fellow generates structured documents with citations linked directly to source materials, ensuring traceability and accuracy.
  3. Ask Fellow drafts context-aware follow-up emails based on meeting discussions, ensuring stakeholders receive timely summaries of decisions, action items, and next steps. The AI references specific agenda items, commitments, and deadlines to minimize manual post-meeting work.

Problems Solved

  1. Ask Fellow addresses the inefficiency of fragmented meeting workflows, where critical insights are lost in siloed notes, follow-ups are delayed, and decisions lack transparency. It consolidates meeting data into a unified system to prevent redundant discussions and missed commitments.
  2. The product targets professionals and teams in fast-paced environments, particularly managers, executives, and cross-functional collaborators who require rapid access to meeting context. It serves industries like tech, marketing, and operations where meetings drive critical outcomes.
  3. Typical use cases include generating board reports from quarterly reviews, resolving project bottlenecks by analyzing past discussions, and automating follow-ups after client calls to maintain alignment without manual note-taking.

Unique Advantages

  1. Unlike standalone transcription tools or note-taking apps, Ask Fellow combines meeting memory with execution capabilities, linking insights directly to actionable outputs like emails or reports. Competitors lack its end-to-end integration of search, analysis, and automation.
  2. The "X-ray & Reasoning" feature innovates by providing traceable citations for every AI-generated insight, allowing users to validate recommendations against original meeting transcripts or recordings. This transparency builds trust in AI-driven outputs.
  3. Competitive advantages include enterprise-grade security with encrypted data storage, compatibility with major calendar and collaboration tools, and adaptive learning that improves recommendations based on organizational meeting patterns.

Frequently Asked Questions (FAQ)

  1. How does Ask Fellow ensure the security of meeting data? Ask Fellow uses AES-256 encryption for data at rest and in transit, adheres to GDPR and CCPA compliance standards, and offers role-based access controls to restrict data visibility to authorized users.
  2. Can Ask Fellow integrate with existing productivity tools? Yes, it syncs with Google Workspace, Microsoft Teams, Zoom, Slack, and project management platforms like Asana, ensuring seamless workflow integration without disrupting existing processes.
  3. How does the AI validate its recommendations? Every insight generated by Ask Fellow includes hyperlinks to timestamped transcript snippets or recording segments, enabling users to audit the source material and verify accuracy before acting on suggestions.

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