We built Qonverge because we had the problem ourselves. A consulting business runs on one question: who is available, and who fits the assignment on the table this week? Spreadsheets and memory answer it until the business grows. Qonverge is an AI talent matching platform for consulting firms, sourcing companies, HR teams and recruiters, now a product other companies use, at qonverge.se.
What it does
Briefs arrive as prose, CVs in a dozen layouts, and keyword search matches strings, not meaning. Qonverge turns both sides into comparable representations and keeps them current. It reads a brief into explicit requirements, represents each person by skills, trajectory and availability rather than job title, and scores profiles against a need with the reasoning attached. An AI call assistant runs first-round phone interviews, tests technical knowledge and collects salary expectations, so the first conversation happens for every candidate, not the first six a human had time to call.
What we ruled out
One hosted model doing everything. Talent data is sensitive, the workload is continuous, and an upstream price change would land on our unit economics. We built it the way we tell clients to in our reference architecture for sovereign ML. Opaque scoring. Recruitment is a sensitive context under the EU AI Act, so every match carries its reasoning and a human decides; see turning the EU AI Act into engineering tickets. Casual handling of candidate data. Residency, retention and erasure were architecture decisions from day one. And the assistant gathers information; it never decides who progresses. Candidates know it is automated, and a recruiter reviews everything.
Qonverge runs on infrastructure we operate, under EU jurisdiction, on an open-weight stack wherever the workload allows. A provider changing its terms costs us a migration, not a rebuild. When we tell a client production machine learning should be portable, auditable and operable by their own team, this is the system we point at.
Who is using it
Qonverge runs in production for consulting firms in Sweden. Two agreed to be named.
Qonverge gave us the horsepower of an entire resourcing team without the overhead. We can finally focus on clients instead of inbox triage.
With Qonverge we don't waste time searching for assignments or preparing applications. It automatically matches our consultants to the right opportunities, letting us focus on delivering value.
Both quotes describe a change those teams feel. Neither is a measurement.
We publish numbers measured against production data, or we publish none.
We are measuring time from brief to shortlist, how much of the bench a search surfaces, and how often the matched candidate is the one placed. When those numbers mean something, this note becomes a case study. If you are weighing something similar, book a call.