Julie Desk, a French startup that’s developed an AI-driven “virtual assistant” to automate the scheduling of meetings, appointments, and more, has..
Julie Desk, a French startup that’s developed an AI-driven “virtual assistant” to automate the scheduling of meetings, appointments, and more, has picked up €2.5 million in new funding — money it plans to use to further develop the technology. Backing the company this time around are previous investor SIDE Capital, Entrepreneur Venture, and SAAS Lab.
In some ways similar to U. S. competitor X.ai, Julie Desk can be thought of as a machine learning-based replacement for a PA. You simply CC “Julie” at the start of or during an email thread with the person you want to schedule a meeting with, and, in theory, the virtual assistant will take care of the rest.
This includes offering up potential meeting times — pulled in from the various online calendars supported — confirming the agreed time and place, adding it to your schedule and sending out the appropriate calendar invites.
The technology also ties into restaurant bookings, and Julie Desk has further integrations planned. This includes support for Skype for Business to create call URLs on the fly for scheduled conference calls. Another potential tie-in, but one that is further in the future, is automating travel bookings, something that other AI-powered virtual assistants have tried before.
“Once you integrate with a person’s calendar, there is a lot more you can do, ” Julie Desk co-founder and CEO Julien Hobeika tells me.
One other interesting aspect of Julie Desk — and something Hobeika is refreshingly candid about — is that the startup openly operates a hybrid model, with its AI being underpinned by continuous human supervision. It sees a human check every final appointment made and editing the very few that aren’ t correct, whilst in turn further training the startup’s algorithms.
This, says the Julie Desk founder, is both necessary for quality assurance purposes, and is also a huge selling point around trust, which is particularly relevant for larger corporate customers where a failure in scheduling could cost customers.
