Spark → Craft → Scale: Learning with machines to drive purchase
Brand + machine learning, working together
Performance isn’t a mystery—it’s a signal problem. We built Crave ML, a human + AI system that uses computer vision + machine learning to learn what drives purchase, then turns those learnings into repeatable creative output—fast enough to keep up with the market and structured enough to scale.Years later, this has evolved into BrandSynth, an AI assistant, insight engine, modular creative orchestration system with ethical governance. Designed for purchase-driven learning, fast iteration, and scalable content volume delivering lower cost-per-asset and higher margin.
Make it last—without losing the plot.
We created a closed loop from behavioral signals → insights → creative variations → outcomes, so learning compounds instead of resetting every campaign. The system helped teams move from “nice ideas” to repeatable, measurable creative performance—with the guardrails to scale responsibly. Across multiple clients, this has delivered 6× ROI, 3.5× engagement and 60% reduction in time-to-first-asset.
