Self-Improving Ecosystem
Entire product stack with an autonomous feedback loop: the system monitors its own lead quality metrics and retrains models.
The Challenge
LeadUp's lead generation models were degrading over time as market conditions changed. Manual retraining was expensive and always reactive — by the time they noticed performance drops, they'd already lost weeks of potential revenue. They needed a system that could adapt autonomously.
The Solution
We architected a self-improving ML ecosystem with continuous feedback loops. The system monitors key performance metrics in real-time, automatically triggering model retraining when it detects drift. Shadow models are trained and A/B tested automatically, with winning models promoted to production without human intervention.
Key Results
Achieved 12% month-over-month performance improvement compound
Eliminated manual retraining — system updates models daily
Reduced model degradation incidents from monthly to zero
ROI increased 340% over 12 months through compound gains
Tech Stack
“Our AI gets smarter every day. We literally wake up to better results than we went to sleep with.”
Ready to build the impossible?
Let's discuss how autonomous systems can transform your operations.