Subnet Session with Arshum, Dimitri & Max from Bitrecs: Subnet 122

Revenue Search returns with the usual banter (and a bit of tech lag) before welcoming Bitrecs (Subnet 122)—a small, doxxed team building an LLM-powered product recommendation engine for e-commerce, starting with Shopify. Dimitri (CEO), Max (CTO) and Arsham (CRO) explain how their widget boosts store performance by generating smarter “you might also like” suggestions, then cleaning messy LLM outputs with a consensus/ranking layer. They show live examples on real stores, including a unique feature: explanations (“reasoning”) displayed to end-users for why each recommendation was chosen.

They also introduce Bitrecs V2, which separates the product into a fast Web2 inference layer (serving real-time recommendations) and a Bittensor “intelligence” layer where miners compete in a winner-take-all prompt-template (“artifact”) evolution game. Bitrecs shares business traction (~130 customers), metrics (avg ~$32/month ARPU, ~$75 CAC, ~1% lift so far with a goal of 2–5%+), and a clear growth plan: deploy a six-figure marketing budget, aim for ~1,000 stores, ship a self-serve API for non-Shopify/enterprise use, and (once trust + lift improve) transition toward performance-based billing / revenue share so stores pay only on measurable uplift.