Canonical provides an AI‑enhanced risk stack for Stripe merchants, offering both managed services and self‑serve tools that add deep device, network, and session signals to PaymentIntents. Their solutions include custom Radar rule engineering, automated dispute workflows, and AI‑driven fraud investigations, helping merchants reduce false positives, lower chargeback rates, and respond to fraud incidents faster.
Funding
Funding not disclosed
Founders
Product
Problem
Merchants using Stripe often rely on default Radar rules that lack access to deep device, network, and session signals, leading to missed fraud patterns, high false positives, and costly chargebacks, especially in high‑value or high‑volume verticals.
Solution
Canonical (gocanonical.com) offers an AI‑enhanced risk stack built by former Stripe Merchant Risk operators. The company provides both managed services—custom Radar rule engineering, automated dispute workflows, and AI‑assisted fraud investigations—and self‑serve tools that enrich PaymentIntents with device fingerprinting, session intelligence, and network data. Their Shield product adds these signals via a lightweight front‑end snippet, enabling more precise rule creation and AI‑driven rule recommendations. Chargeback AI automates dispute response by generating reason‑code‑specific rebuttal letters and evidence audits directly from Stripe data. Together, these solutions give merchants actionable signals, faster incident response, and reduced dispute rates across multiple industries.
Target Audience
Primary customers are Stripe‑based merchants and platforms—such as e‑commerce retailers, marketplaces, SaaS providers, and high‑value goods sellers—who need advanced fraud detection, automated dispute handling, and custom risk controls.
Features
- Custom Radar rule engineering using proprietary device, behavioral, and velocity signals unavailable in standard Stripe tooling
- AI‑assisted fraud investigation that surfaces synthetic identities, coordinated attack vectors, and revenue impact analyses
- Shield fraud prevention tool: one‑line front‑end integration (15 KB) that enriches every PaymentIntent with device, network, and session data for real‑time risk scoring
- AI‑powered rule recommendation engine that continuously adapts to emerging fraud patterns
- Chargeback AI Claude Code plugin that generates submission‑ready rebuttal letters, performs evidence gap analysis, and supports reason‑code‑specific responses with zero code
- Free domain scan that identifies potential fraud vectors without requiring Stripe account connection
- Deployment across 10+ industries with documented fraud reduction (e.g., 47 % average dispute reduction) and over $30 M in prevented fraud