We wanted recruiters to spend their working day on people, not on the software that records them.
Jonathan and Sho met in recruitment at Uber, hiring into several markets while the company was growing quickly. It taught us what hiring looks like when speed matters and a slow process costs you the person.
We left to start our own recruitment agency, working mainly with technology companies. We still work on roles there, which is the reason this product exists at all.
The same candidate lived in three places. A good call was followed by twenty minutes of writing it up, and then a reminder set somewhere else so the follow-up would actually happen. None of that work is recruiting, and all of it has to be done.
We tried the established CRMs and added tools around them. Every addition was another place the truth could hide, another subscription, and another thing to keep current. The admin grew faster than the agency did.
A recruiter's advantage is the relationships they hold, and those are built in conversations. So the ambition is simple to state and hard to do: the software should absorb as much of the work around those relationships as it credibly can, and hand back the hours.
That is what AI is for here. Reading a CV, writing up a call, finding the person you already met two years ago, remembering March. The judgment stays with the recruiter, who decides who to call and what to say.
Our recruitment team uses Connekt every day. We use it to find candidates, manage conversations and follow up. That gives us a direct view of what helps and what needs work.
It also sets the order we build in. When something slows our own recruiters down we hear about it the same week, and it goes near the top of the list. It is a short feedback loop, and it keeps us honest about which features actually earn their place.
Connekt is a small team and we hire slowly. People here own whole problems rather than slices of them, and demos are run by the founders rather than a sales function.