ZapMart ExperimentOS

ZapMart ExperimentOS closes the loop no q-commerce platform has closed — from real-time behavioral signal to promotional content, fully autonomous, zero manual handoffs. Today, Blinkit and Zepto run A/B experiments manually. Swiggy's XP platform automates metric computation but hypothesis generation, decisions, and content briefing remain human work. ExperimentOS automates all of it. Seven Band agents coordinate through a shared context layer: Signal Agent detects conversion drops, cart abandonment spikes, and reorder gaps exceeding confidence thresholds. Hypothesis Agent selects interventions using historical win rates and generates structured hypotheses via Gemini AI. Experiment Design Agent produces CUPED-adjusted sample sizes, variant designs, traffic allocation, and early stopping rules. Integrity Agent monitors for SRM via chi-square detection, enforces novelty windows, and auto-pauses invalid experiments. Results Agent computes statistical significance, effect sizes, confidence intervals, and plain-language readouts. Decision Agent makes go/no-go recommendations with graduated rollout plans and publishes learning signals. Promotional Content Agent generates push copy, homepage banners, and cart banners from winning results — no human brief needed. Band is the nervous system. Agents publish structured context and subscribe to what they need. The Integrity Agent can pause mid-flight and every downstream agent responds immediately. Full reasoning trace visible in real time. Three demo scenarios: dairy conversion drop, cart abandonment with SRM detection and human resume, reorder gap with two-arm results. Built solo in 7 days. Inspired by running 40 experiments/month manually at Snapdeal — and what that workflow looks like when agents replace every manual step.