PayLens: Multi-Rail Revenue Recovery

PayLens is a deterministic capital reconciliation engine and grounded AI Deal Desk built for omnichannel e-commerce merchants operating across fragmented payment rails. THE COMMERCE PROBLEM: Modern online brands sell on digital storefronts (Shopify, WooCommerce) but collect revenue through disconnected channels: credit card payment gateways (Stripe), bank wires (SEPA), and courier cash-on-delivery remittances (DHL, FedEx). When payments settle on independent schedules or fail silently, merchants lose 3-7% of gross revenue to ghost dispatches, courier shortfall deductions, and stockouts on hero SKUs. OUR ARCHITECTURAL RULE - CODE COMPUTES, MODEL EXPLAINS: PayLens eliminates LLM hallucinations by splitting compute into two strict tiers: Deterministic Core (DuckDB + statsmodels): 100% of arithmetic, ledger matching, and 7-day Holt-Winters demand forecasting is calculated deterministically before any AI call. Grounding Shield: A regex numeric token verifier inspects model text, guaranteeing that every numeric token matches underlying DuckDB tool outputs with zero ungrounded digits displayed. AMD HARDWARE INTEGRATION: • Live Hosted Inference: Powered by AMD Radeon Cloud TokenFactory serving DeepSeek-V4-Flash, scaling from 18.2 output tok/s (c=1) to 62.9 tok/s (c=4) with a 906ms live ping. • Dual Reasoning Layer: Google AI Studio Gemma 4 REST provides instant reasoning failover (293ms latency). • Self-Hosted Enterprise Recipe: Full production deployment scripts for AMD Instinct MI300X (192GB HBM3) on ROCm 7.2.1 and vLLM. VERIFIED RESULTS (DEMONSTRATION DATASET): Across a 20-store network, PayLens identified $10,975.00 in leakage, including $4,052.50 on Store 01. An honest stress-test split on 30 synthetic transactions yielded a 0.933 F1 score (28 TP, 2 FP, 2 FN), transparently accounting for delayed SEPA wire settlements.