Applied ML for programmatic advertising.
Machine learning is how programmatic advertising achieves efficiency at scale — in floor pricing, supply paths, pacing, fraud, and agentic media buying.
This is your problem.
Three structural pains that hit every AdTech company trying to build custom ML.
Auction yield is leaking.
Floors, supply paths, and pacing run on rules — not learned signals. Each percent of leakage compounds across billions of bids.
Generic ML stacks don't fit programmatic.
Sub-10ms inference, billion-scale event volume, drift in hours not weeks. Notebook ML never reaches production.
Agentic buying is here. Your stack isn’t.
LLMs are reshaping media buying and RTB. Without custom models on your data, you ship a wrapper — not a moat.
This is what we do.
Auction ML, production infrastructure, and agentic systems — built on your data. Tap a node to see the capability.
Three ways to engage.
Simulator
Test bidding, pacing, and pricing logic against realistic auctions before live traffic.
Latest Research
Recapturing the English Auction: Sequential Floor Optimization Within User Sessions in Programmatic Advertising
From Clicks to Conversations: Why AI Chat Is Advertising's Real Frontier
Toward Information Symmetry: A Bilateral Disclosure Framework for First-Price Ad Auctions
Ready to build?
No pitch decks, no generic demos — just a technical conversation about your data and your goals.