D2C AI Employee
E-Commerce Margin Leak Detection Agent

An AI agent for e-commerce connects to your business data sources — Shopify orders, payment processors, logistics providers, and ad platforms — and lets you ask natural language business questions. D2C AI Employee goes further by enforcing guardrails: every answer it gives is backed by real SQL query results, not LLM guesses about your business metrics.

Anti-hallucination SQL execution means the agent cannot make up data. When you ask "What was my margin on Shopify orders last month?", the agent generates a SQL query, executes it against your real Supabase database, and returns the verified result. Every figure is source-traceable — you can see exactly which query produced which number. This prevents the common LLM problem of generating confident but incorrect business metrics.

Guardrails are validation layers that intercept LLM outputs before they reach the user. In D2C AI Employee, if the LLM attempts to state a metric without calling the appropriate MCP tool first, the guardrail blocks the response and forces a tool call. This ensures all business data claims are substantiated by actual data retrieval, not language model inference.

Margin leak detection identifies where revenue is being silently eroded between gross sales and net profit. Common leaks include excessive Meta Ads spend that isn't offset by sales lift, high Shiprocket logistics costs on low-margin orders, Razorpay refunds that haven't been reconciled against Shopify orders, and discount stacking. D2C AI Employee correlates all four data sources to surface these patterns automatically.