Fellow

Fellow is an AI meeting assistant and notetaker for teams and organizations that need reliable meeting notes, searchable records, and accountable follow-through from everyday conversations. It records meetings, can transcribe audio, summarizes discussion, captures decisions, and turns action items into usable context for the people who were in the room and the people who were not. At its core, the platform treats meetings as an operational knowledge source rather than a one-time calendar event. A discussion can become a transcript, an audio summarization, a concise recap, and a structured record of what was agreed. That makes it useful for recurring team meetings, executive reviews, customer conversations, hiring panels, project updates, and cross-functional planning. For managers and team leads, the value is in continuity. Meeting notes do not disappear into private documents or scattered chat threads, and follow-ups are easier to track after the call ends. Fellow helps teams preserve the reasoning behind decisions, not just the final task list, which is important when work spans departments, time zones, and multiple stakeholders. Governance is a central part of the product’s identity. Fellow is built for organizations that need control over how meeting records are created, stored, accessed, and retained. Permissioned access, audit trails, redaction capabilities, and retention options such as zero-day retention make the platform more suitable for enterprise and regulated environments than lightweight personal note takers. AskFellow extends the meeting archive into an AI knowledge layer. Instead of manually searching through transcripts or asking colleagues to repeat what happened, users can query past meetings and retrieve relevant answers from authorized records. This shifts the meeting assistant from passive documentation toward an internal agent that helps teams reuse institutional memory. In regulated or privacy-sensitive settings, the emphasis is not only on convenience. Legal, financial, healthcare, public sector, and enterprise teams often need evidence of who accessed information, what was captured, and how long records were kept. Fellow positions itself around these requirements by combining AI-generated meeting intelligence with centralized administrative control. Revenue, customer success, and operations teams can also benefit when meeting outcomes need to connect with broader workflows. The platform’s structured decisions and action items can support handoffs, follow-up processes, and CRM automation workflows when paired with the systems a team already uses. The practical aim is to reduce the gap between what was said in a meeting and what happens afterward. Rather than being only a transcription utility, Fellow is best understood as a meeting intelligence platform for organizations that want AI assistance without losing governance over sensitive conversations. Its story is about making meetings more usable after they happen, while giving administrators the controls needed to deploy that capability at scale.