Fraud prevention for the agent economy
To your fraud stack, they look identical. xkeeper tells them apart — scoring every actor at your gate, and showing you exactly why.
Illustrative data — in production, this is your traffic.
The problem
Legacy fraud tools sort traffic into two buckets — humans get through, bots get blocked. Here’s how that verdict goes wrong, three ways.
Still most of your traffic — still gaming promos and referrals, at human speed.
Shopping and redeeming on a real customer’s behalf. Real intent, real revenue.
Malicious automation that looks human to legacy tools — card testing, promo farming, account takeover.
Block a pattern today and it mutates by next week. Fraud has always been a cat-and-mouse game — and the mouse now has AI.
So xkeeper puts a keeper agent on watch — surfacing new patterns as they emerge, then reporting, acting, or adapting your rules as the game shifts. You set how much it does on its own.
The questions that matter now: who is this actor, who do they act for, what are they allowed to do — and what will they try next? That takes a fraud engine built to ask, answer, and adapt.
The product
Fraud tools ask you to trust a number. xkeeper shows its work — every score explained, every factor tunable, every agent action logged.
Each decision carries a plain-language factor breakdown — what contributed, by how much, and why. Audit-ready by default, for your team and your regulator.
Your risk tolerance isn’t ours to decide. Reweight the factors that matter to your business, version your policies like code, and roll back when an experiment doesn’t pan out.
Payment fraud, promo abuse, account takeover, one specific campaign — run separate models per use case or cohort instead of forcing one score to mean everything.
Bring your own events. Trigger rules on anything you can send us — a signup, a redemption, a custom signal only your product emits.
Devices, cards, emails, phone numbers — shared fingerprints connect “unrelated” accounts into rings. xkeeper maps every connection, and keeper agents walk the graph at machine scale, finding clusters no human could piece together case by case.
Task an agent to monitor a cohort, surface emerging patterns, file reports — or adapt your rules and act, with autonomy you dial up or down. Every action logged, every conclusion explained. 24/7.
Developers
One SDK, one call per event. Send us the request — with whatever signals ride along: agent credentials (KYA), checkout-protocol context (ACP), device, your custom fields. Back comes a score, an action, and the reasons — as data, not a dashboard screenshot.
No sales call to see the product. No six-month integration. Docs, keys, and a sandbox from day one.
$ npm install @xkeeper/sdk
import { xkeeper } from "@xkeeper/sdk";
const decision = await xkeeper.evaluate({
event: "promo.redeem",
actor: req, // headers, device, credential
context: { code: "SPRING24" },
});
decision.action // "block"
decision.score // 94
decision.because // ["credential_fails_verification",
// "redemption_velocity_22x_cohort",
// "device_linked_to_41_accounts"]Use cases
Card testing, stolen credentials, chargebacks — at human and agent speed.
Referral farming, coupon stacking, signup bonuses milked by fleets of agents.
Credential stuffing and session hijacking, including agents with stolen delegation.
Drop-day bots, bonus hunters, one-campaign scams — spin up a model for the moment, retire it after.
Fake reviews, spam listings, and synthetic engagement at generative scale.
Early access
The agent-payment rails made one thing explicit: the fraud decision is still yours. We’re onboarding a small set of design partners — tell us what’s hitting you hardest and we’ll be in touch.