I made a mistake; apparently Glean uses knowledge graphs too: https://www.glean.com/resources/guides/glean-knowledge-graph
This raises a follow-up question: what is your differentiation?
This raises a follow-up question: what is your differentiation?
The main thing we see in the world is that (a) teams already struggle to coordinate information over many different personalities and data sources. This was a more dull problem before when the actual IC/execution overhead was so large. But now with AI the execution overhead is way smaller, and "being on the same page" is a much bigger problem. (b) As agents do more and more of the mechanical work in the company, it's vital that they have a consistent big picture-view to perform tasks efficiently without errors.
Hyper aims to solve this problem end-to-end; the memory system is a vital part of this, but Hyper does more. We already support native agentic email-writing and LinkedIn-drafting automations, and will be expanding on that front. Today it's a "brain that knows everything," but so much of the value is in using that brain to perform work in a self-improving way. And on the other side, we need to make sure that getting information into the system is as frictionless as possible. We care a ton about UX -- one-click integrations, using hooks to get context in and out invisibly and reliably.