Cozu provides a voice‑first work journal that captures employees’ tacit knowledge through real‑time speech transcription and AI‑driven summarization, eliminating the need for manual note‑taking. Workers record what they did, receive intelligent follow‑up prompts, and get clean, shareable summaries while earning points redeemable for bonuses, PTO, or recognition. The platform targets knowledge‑intensive teams in manufacturing, R&D, and specialty chemicals, helping companies preserve expertise during retirements, restructurings, or acquisitions.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises lose critical tacit knowledge when employees retire, are transferred, or work remotely, because informal knowledge transfer mechanisms like watercooler conversations are no longer available. Capturing this expertise traditionally requires manual documentation, which is time‑consuming and often ignored by busy workers.
Solution
Cozu provides a voice‑first work journal that lets employees record what they worked on by speaking, while an AI engine transcribes the audio, asks contextual follow‑up questions, and produces a clean, shareable written summary without any typing. The system rewards contributors with points that can be redeemed for bonuses, paid time off, or recognition, creating a personal incentive to contribute. By continuously learning each user’s workflow, the AI improves its questioning and summarization over time, building a searchable knowledge repository that maps expertise to individuals. This approach turns routine work reflections into a structured knowledge base that can be accessed instantly, reducing the risk of knowledge loss during retirements, mergers, acquisitions, or restructuring.
Target Audience
Primary customers are large enterprises and mid‑size companies in sectors like manufacturing, research and development, and specialty chemicals that rely on expert knowledge and face high turnover, M&A, or remote‑work environments.
Features
- Voice capture interface with real‑time transcription and automatic generation of written summaries
- AI-driven follow‑up questioning that refines captured information and ensures completeness
- Point‑based reward system redeemable for tangible benefits such as bonuses, PTO, or recognition
- Searchable knowledge graph that links summaries to experts and enables instant retrieval of institutional knowledge
- Continuous learning model that adapts to each user’s processes, improving question relevance and summary quality over time
- Integration‑ready design that fits into existing workflows for manufacturing, R&D, specialty chemicals, and other complex‑task teams