Laurence

RL for performance marketing

Winter 2026ActiveB2BAnalyticsArtificial IntelligenceMarketingAdvertisingTrading

Company

Advertising today is like trading in the 1980s pits: archaic, manual, and iterative guesswork. Humans update bids and keywords using noisy, delayed data with fixed rules that both break at scale and ignore stochasticity. We've built quantitative systems that advertise the way modern hedge-funds trade markets: continuous decision-making under stochastic outcomes and explicit profit constraints. We use customers' existing ad copy and use reinforcement learning and train our own LLMs to run ads on autopilot, harvesting profits when we’re confident and borrowing signals from similar keywords when data is sparse. Starting with brands on Amazon, we are automating tens of millions in live ad spend, increasing gross sales while decreasing advertising cost of sales by 40%.

Verdict

High Signal

Market Opportunity

Amazon advertising is a $50B+ annual market growing rapidly; Amazon PPC management (agencies + software) is a multi-billion dollar segment with thousands of SMB and enterprise brand customers. ICP is clear: CPG brands and SMBs selling on Amazon spending meaningful monthly ad budgets. Monetization path is obvious — performance fee or SaaS on managed ad spend.

High Signal

Founder Signal

Matthew Chen has direct ML engineering experience at Google (built Data Science Agent) and Meta (grew new user retention 18%, tuned friending model), plus Math+CS/AI at Cornell — directly relevant to the product. Leo Gierhake is a researcher at Jump Trading (executed billions in daily crypto volume), EE at ETH Zürich, and has early crypto founder experience (Teragon, POKKET); his quant background is the core technical moat. Together they span ML at big tech and quant trading — exactly what the product claims to do.

Medium Signal

Competition

Competes directly with Amazon PPC automation tools like Perpetua, Helium 10 Adtomic, Pacvue, Teikametrics, and Scale Insights — all established players with significant customer bases. Also displaces PPC agencies. Differentiation is the RL/quant approach vs. rule-based automation, which is real but not impossible for well-funded incumbents to replicate. No proprietary data moat cited, but hourly optimization and statistical modeling are genuine differentiators if the results hold.

High Signal

Product

3 named customer logos: Because Market, Finn (Pet Finn), Flings (Eat Flings). 3 testimonials from founders of named brands with specific metrics (2x sales growth, 50% sales growth, 2x to 5.78x ROAS improvement). Detailed feature descriptions and case studies. Book a Demo CTA. No pricing page visible.

OverallA Tier

Strong founder-market fit: a Google/Meta ML engineer paired with a Jump Trading quant researcher building quantitative ad optimization. The product has 3 named customer logos (Because Market, Finn, Flings) with specific ROI metrics in testimonials (2x sales growth, 50% growth, 2x to 5.78x ROAS improvement). Three high signals (product, founders, market) with medium competition. Named customers with quantified results are strong validation. One of the better-evidenced companies in the batch.

Active Founders

Matthew Chen

Founder

Built the Data Science Agent at Google. Grew Facebook new user retention by 18% while tuning Facebook's friending model. Third engineer at health-tech startup. Math+CS & AI research at Cornell. Ex-national team and semi-pro soccer goalie. Washed dishes and waited tables to pay for college. Financially independent at 17. National team & semi-pro soccer goalie. Taught myself to code at 18. Chemistry research at 15. CEO

Leo Gierhake

Founder

Researcher at Jump Trading, building quantitative models to execute 50% of all global crypto trades. $250,000 in high-stakes professional poker winnings. Founded a crypto investing platform at 18. ETH Zurich Electrical Engineering Chief Scientist

Laurence

TierA Tier

BatchWinter 2026

Team Size2

StatusActive

Last Updated2 days ago

Disagree with this rating? Let us know