A single place for everything we aligned on after today's deep dive — the commercial offer for review and comment, the platform materials, the Exepay rule-migration path, and the calendar for the follow-up. All in one link.
Add-on path: Merchant Initiated Fraud (MIF) can be added later with a simple email request — the contract includes the option so you're never locked out of the next capability.
The proposal is live in Canva. Open it, walk through the pricing and the terms with the team, and leave comments directly on the document — I'll see every comment and reply inline, so we can iterate without a chain of emails.
Direct contract, PFD scope, 100K calls/month, 5 seats, 1-year term. Everything we discussed, priced and structured.
The integration mirrors the setup your partner already runs — Hypergate as the gateway, Exepay as the acquirer, Fraudio inline on the risk layer. Same architecture means the same operational path Ryver's team is already familiar with, no new patterns to learn.
Payment gateway
Real-time fraud decisioning
Acquirer
We'll perform a gap analysis on the current Exepay rule set and replicate it into Fraudio so nothing changes operationally on day one. Your existing risk posture is preserved — no need to re-open every policy discussion from scratch. Once the platform is live, the rule library, LLM rule generator and shadow-mode testing are yours to tighten or extend at whatever pace fits the team.
The audit function in the rule editor also prevents accidental over-restrictive rules — the platform warns you if a new rule would block excessive legitimate volume before it goes to production. The kind of 40%-of-book-cut experience you mentioned won't happen here.
Volume statistics filterable by merchant and MCC, average transaction amounts, decline rates, chargeback ratios — and comparison against peer-MCC benchmarks.
Screening rules (real-time, event-driven) and monitoring rules (entity-driven — merchants, IPs, other entities). Test in shadow mode against historical data. Audit function catches logic errors before production.
Active, unassigned, snoozed and shadow queues. Alerts ship with clear reasoning — rule- or AI-generated. Mark transactions as good or fraud to feed the ML models directly.
LLM-generated summaries of web-scraped merchant information — smart context on what each merchant actually sells, versus what their MCC claims.
Email pushes, webhooks, automated fund withholding based on fraud triggers. Sub-tenant creation for managing multiple merchant environments cleanly.
Fraud notifications, chargebacks and Visa / Mastercard programme ratios tracked in the refund and dispute area — the metrics that decide merchant standing with the schemes.
Comment directly on the document. I'll reply inline.
Full API reference, integration guide, data schema, webhook specs.
Centralised AI, network effect and customer results on a single page.
Grab a slot for the sign-off call or any question along the way.
Comment directly on the offer: Canva supports inline comments — highlight any line, add a note, tag me if you need a response. I'll iterate on the document with you rather than sending a new PDF for every change. When we're aligned, I'll draft the order form.