Let's admit it : knowledge is scattered in many tools note, chats, mail... Enterprise servers are cluttered, the more content there this, the more folders and subfolders you get, and harder it get the right information. It's hard time to take advantage of graph capabilities to take back control.

What it does

When you make a web search we blend Google results with content from your graph knowledge base. This is made possible by a chrome extension and our insight engine that take full advantage of the graph to auto-organize content and increase collective intelligence. Our web app rethink the way we explore enterprise content. It provides expert feeds of information based on specific tags, thus focus on your interests and we break information silos. Wait there is more integrate our insight engine into a Slack Smartbot and a Office app is coming next.

How we built it

We used the grand-stack, typescript and next.js to build a API, a web app and an extension.

Challenges we ran into

The community is a great help, yet we still need more examples of working applications. One complexity is to keep the graph-model clear and as simple as possible. We used a second graphql layer to make the business logic and use typing.

Accomplishments that we're proud of

We managed to show the value of Neo4j for knowledge management and some exciting integration with Google Chrome and Slack.

What we learned

We heavily used the grand stack and used neo4j-graphql to build the knowledge base and provide CRUD barely using Cypher ;) We made huge progress in using graphql for development.

What's next for

Our goal is to build a productivity assistant for knowledge workers : consultant, engineers, marketers. Next steps are 1/ building native integration with more tools like Office 2/ take advantage of graph algorithms to provide recommandations, visualization and a contextual experience

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