Multi-attribute matching engine
AI relationship mapping across lifestyle, goals, values, and behavioural compatibility signals.
Case Study · SOCIAL NETWORKING · UK
Nuancers: Robo-advisory matchmaking
AI matching with robo-advisory logic.
The story
What Nuancers needed, and what we built.
Sonia Lalvani (Citi, Cambridge) wanted to build a matchmaking platform applying robo-advisory-style logic to relationships rather than the swipe-and-hope model. KUMO designed the AI matching engine and platform architecture, robo-advisory-style compatibility scoring, lifestyle and goal matching.
What we delivered
Six areas of production work.
Robo-advisory-style scoring
Compatibility models adapted from advisory logic, quality of fit over volume of matches.
Curated connection suggestions
Limited, high-quality matches surfaced over time rather than infinite swipe queues.
Profile capture flow
Structured onboarding designed to capture the signals the matching engine actually needs to score well.
Premium UX for a discerning audience
Design and pacing built for a high-trust, low-volume product, not viral growth loops.
Privacy-first architecture
Sensitive profile data isolated, role-based visibility, and minimal data exposure to the model layer.
Highlights
Project highlights.
More work.
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