DisputeIQ.

The problem

Chargebacks are bleeding e-commerce margins. Global chargeback volume exceeds $100B annually, and 60–80% of chargebacks are "friendly fraud" (customers disputing legitimate transactions) — meaning evidence quality, not fraud detection, is the deciding factor in outcomes.

The Sarah workflow today is brutal: receives the chargeback notification (5 min, buried in inbox, 7–10 day deadline starts immediately) → identifies the reason code (5 min, codes are cryptic) → compiles evidence across Shopify, Stripe, UPS/FedEx tracking, customer service tickets (20 min, manual) → drafts the response (10 min, no template) → submits to the processor (5 min). ~45 minutes per dispute × 80 disputes/month = 40 hours/month — and merchants still lose 20–30% of winnable cases because they miss a required evidence field for the specific reason code.

The solution

DisputeIQ automates the entire lifecycle. Pre-ship: orders are scored on fraud signals before fulfillment; high-risk orders are flagged for verification. On dispute receipt: the system retrieves the reason code's exact evidence requirements (via LLM + RAG over the requirements matrix), automatically aggregates evidence from connected systems (Shopify, Stripe, shipping carriers, customer service tools), and predicts win probability so Sarah only fights the disputes worth fighting.

For winnable disputes, the processor-ready evidence package is generated automatically in the format card networks expect — turning 45-minute manual submissions into 3-minute reviews. At $99/month entry, the product is priced for the SMB merchants that Chargeflow's $499+ minimum prices out.

How it works

Two-stage flow: Stage 1 (Pre-Transaction) — new order → risk signal scoring (device risk, IP match, velocity, AVS/CVV) → risk decision (Low / Medium / High → proceed / flag for review / alert merchant). MVP uses rules-based scoring with Claude reasoning on edge cases. Stage 2 (Chargeback Lifecycle) — chargeback received → reason code classified → evidence requirements retrieved from matrix → evidence aggregated across systems → validation against requirements → recommendation (SUBMIT / ABANDON / REVIEW / PENDING) with win probability → generated evidence package → submission.

Two-model Claude strategy: Haiku in production ($0.25 per 1M input tokens, optimised for high-volume scoring); Sonnet for evaluation and development (prompt iteration, LLM-as-judge for win-probability calibration). Architecture: n8n orchestrates the workflow; Claude handles the structured reasoning per stage. 20 synthetic test cases across 4 categories: winnable disputes (10), unwinnable disputes (e.g., real fraud), edge cases, negative cases.

Who it's for

Primary persona — Sarah, 28–40: E-commerce Operations Manager at a Shopify Plus merchant (~$3M GMV, team of 3–20). She handles order ops, logistics, customer service, dispute management — everything operational. ~80 disputes/month, ~40 hrs/month on manual evidence compilation, juggling Shopify, UPS/FedEx tracking dashboards, Zendesk, Stripe, and a spreadsheet.

Customer segments: Shopify Plus stores ($500K–$10M GMV), Amazon FBA sellers ($2–$50M sales), subscription box companies (high chargeback risk from recurring billing), digital goods sellers. Buyers: e-commerce business owners, finance leads, operations heads at larger merchants. Purchasing trigger: 50+ disputes/month + 20+ hrs/month on manual evidence compilation.

Why it matters

The chargeback management market is in 20–25% CAGR growth with friendly fraud rising — the structural shift is that evidence quality, not fraud detection, decides outcomes. Stricter issuer/network rules and tightening Stripe / PayPal dispute interfaces are raising the bar on what merchants need to submit; SMB merchants without dedicated dispute teams are losing thousands monthly to disputes they could win if they had the time.

DisputeIQ's structural bet: AI-first, fully automated, SMB-priced beats AI + human hybrid, enterprise-priced for the long-tail merchant segment that Chargeflow can't economically serve. Chargeflow's $50M+ ARR validates the market; DisputeIQ's positioning opens it to the 10× larger SMB segment Chargeflow's price floor excludes.

At a glance

Project

DisputeIQ

Built by

Shirjeel Ahmad & Praveena

One-liner

AI-first chargeback automation for SMB merchants — pre-ship risk scoring, auto-evidence aggregation, win probability prediction, and processor-ready submissions.