And usually nobody in the organisation can see that line. The two rooms sit in different departments, use different vocabularies, and nothing anywhere records that they are related at all.
Drawing that line across a whole organisation takes a new method and new tools. An ontology and a knowledge graph let cross-department relationships be written down properly for the first time. But the tools do not know what should connect to what. Whoever uses them has to understand knowledge management well enough to tell which lines mean something and which are coincidence.
Neo Gens is led by Noppadol Weerakitti. More than 35 years in modern knowledge management across information technology, service design, business development, public libraries and museums — and, for the last two years, a deliberate study of applying AI, ontology and knowledge graphs to the management of knowledge. It looks like unrelated work. It has been the same question every time: how does the knowledge an organisation holds find its way out to the people outside it?
I have worked inside a number of organisations and advised many more. Every time one of them thrived or failed, it came down to the same thing: did the organisation know what it knew, and could it put that knowledge to use? The same holds for a single person.
That matters more now. AI has given everyone equal access to public knowledge, and the advantage that once came from reaching it has become ordinary.
What creates a difference now is the knowledge held inside an organisation, and above all in the organisations sitting on raw material accumulated over centuries. Museums and libraries hold that, and they hold something more: the public extends them a trust it extends to almost nobody else.
People believe museums. People believe libraries. They believe them as the organisations that have led the world in managing knowledge for a very long time, and that belief took a century to build.
So what people will expect from a museum or a library is not merely a chatbot answering basic questions the way every other chatbot does. It is a personal knowledge assistant — one that helps each visitor extend and connect what they already know to what is in the exhibition, in the collection, and in the object in front of them; that opens a new conversation at every step; and that sends them out with new possibilities on every visit.
That is the goal of what we call Modern Knowledge Management. We cannot build it alone, which is why we are inviting the museums and libraries that think the same way to build it with us.
A knowledge layer fails at the seams. A curator's vocabulary meets a conservator's, which meets the archive's, which meets whatever the collections system was configured to accept in 1998. Someone who has only ever worked inside one of those departments cannot reconcile them — and no ontology bought off the shelf knows they disagree.
The firm is named for both halves of that. Neo Gens is neo-generalist and neo-generation at once. A neo-generalist moves along the line between deep specialism and broad knowledge instead of settling at one end, and creates value from the connections across fields rather than from depth in a single one. The other half is who the work is for: a generation that will ask an AI before it asks a museum or a library, and the generation of institutions that has to be ready when it does. It is a way of working before it is a philosophy — and it is the reason the cross-department question is the one we start with.
Neo Gens is not an academic practice. Every line below was a commercial or public-accountability problem before it was a knowledge problem — a budget to defend, an audience to win back, a board to answer to. That is the half most knowledge-management advice leaves out, and it is the half that decides whether the work survives contact with a real institution.
90 minutes. Bring your curators or librarians, and one question your institution couldn't answer.
Or write directly — hello@neogens.co