Currently, the most popular corporate knowledge management system is Confluence by Alatasian. It is known for a lack of search capabilities and makes most corporate knowledge inaccessible, especially in fast-growing companies where regular structure and responsibilities change. Some independent vendors fill this gap by offering carefully tuned solar-based search engines for Confluence, but not real semantic search. Confluence is a proprietary cloud-based solution, and it would be difficult to MVP a search extension in a hackathon. The most advanced open-source alternative is wiki.js, which already supports external search engines. So the current goal is to implement an external search engine for wiki.js using Cohere's LLM-powered Multilingual Text Understanding model and Qdrant's vector search engine. At the second stage of the project (most likely outside the hackathon scope), we plan to add the capability to upload and index videos in our knowledge management system. Recordings of presentations and meetings are the richest source of knowledge, but they were left outside knowledge management due to technical difficulties. Simple transcription and semantic search of that content could significantly boost corporate knowledge accessibility.Category tags:
Knowledge Base, Virtual Assistant, Productivity
"I think that might be a valuable tool, if it supported audio-to-text transcription already. Right now that's just a pure semantic search over documents, but the plans look promising."
"Great user interface design and the results are presented nicely."
"i like the idea of trying to solve the issue of limited search capabilities in corporate knowledge management systems and also trying to implement an external search engine for wiki.js. However, the presentation could have been more concise and it was difficult to understand the application demo without watching the nine-minute presentation"
Co-Founder of Content-Hive