Revenue recovery for subscription products

AI SaaS E-learning Premium B2B

Turn the sharing you already tolerate into paid seats.

Harev helps subscription products detect monetizable account sharing, identify the extra users already getting value, and convert high-confidence cases into legitimate paid seats through native upgrade prompts, not bans or forced logouts.

Request early access See how it works

0% upfront 10–15% on recovered revenue 10-minute SDK Stripe-ready

Founding cohort: limited early-access onboarding for teams that want to validate demand before the full product launch.

The silent leak

Every shared account is value delivered, cost incurred, and revenue left on the table.

Teams share credentials. Students split logins. Agencies stretch one paid seat across multiple people. If your pricing assumes one user per account, tolerated sharing quietly distorts ARPU, breaks usage metrics, and grows infrastructure cost without growing revenue.

5–15%

Typical revenue opportunity range when account sharing is already happening inside a subscription product

What most teams recover today from extra users already getting value through a single paid account

1.4×

Possible infrastructure drag on AI-heavy products when multiple people quietly share one paid seat

How it works

Detect, qualify, and convert without turning your product into a crackdown.

Harev is built around a simple rule: only intervene when the pattern is commercially meaningful, and use the least disruptive move that can turn extra usage into paid expansion.

Collect lightweight usage signals

Add a small JS SDK, optionally send server-side events, and start observing device, session, and behavior patterns without rewriting your product.

Separate real sharing from normal usage

Harev combines browser, geo-distance, concurrency, and product-behavior signals so one person using multiple devices does not look like a team sharing one login.

Convert high-confidence cases into revenue

When confidence is high enough, Harev shows a native upgrade path that turns tolerated sharing into legitimate paid seats or a team plan.

10-minute setup

A lightweight integration for your first signal.

Enough detail to show how the rollout works, without pretending the founding cohort is buying finished shelfware on day one.

Example integration shape founding cohort

import { Harev } from "@harev/sdk";

Harev.init({
  apiKey: "pk_live_xxx",
  userId: currentUser.id,
  plan: currentUser.plan
});

const decision = await Harev.evaluate();
if (decision.action === "SHOW_UPGRADE") {
  Harev.openUpgradePrompt(decision.recommendation);
}

< 30kb gzipped target async + deferred server events supported

Business model

Zero risk to get started.

Founding-cohort customers pay nothing upfront. Harev earns 10–15% of revenue recovered from Harev-attributed upgrade flows, measured against your baseline and agreed during onboarding.

0% upfront software fee
10–15% revshare on Harev-attributed recovered revenue
White-glove onboarding with direct founder access
Founding-cohort input on thresholds, widgets, and rollout

Why buyers care

It aligns incentives from day one.

You do not need to bet on another heavy software contract just to learn whether this problem is worth solving. Harev only wins when new revenue is actually recovered.

Clear positioning

What Harev is and what it is not.

The fastest way to kill conversion here is to sound like an anti-fraud crackdown product. Harev is a revenue recovery layer for subscription businesses, not a punishment engine.

What Harev is

Revenue recovery infrastructure for subscription products
Built to upsell extra users already getting value
Practical for early rollout without a heavy platform project
Aligned to recovered revenue instead of upfront software spend

What Harev is not

A punitive anti-piracy or fraud-enforcement tool
Raw fingerprinting data with no monetization layer
A heavyweight enterprise security rollout
A forced-logout machine that turns ambiguity into churn

Who it’s for

Best fit for products where one seat clearly is not meant for many users.

The first release is aimed at web-first teams with subscription products, clear seat economics, and a real commercial reason to stop tolerating shared usage.

AI SaaS

When shared accounts drive inference cost, every unbilled extra user hurts margin as well as monetization.

E-learning

Courses, cohorts, and communities get shared constantly. Harev gives you a cleaner path than blocking students mid-program.

Premium B2B

If you sell individual plans to teams, Harev helps you turn tolerated internal sharing into legitimate seat expansion.

Best fit today Web-first Stripe billing 5K–100K MAU Single-seat or per-user pricing

Founding cohort

Join the first group shaping Harev before general release.

We are onboarding a small number of early customers who want to validate the opportunity, shape the product, and lock in favorable terms before the public launch.

Apply for early access

Limited cohort • guided rollout • direct founder access

FAQ

The questions every buyer asks first.

The real objections are rollout risk, false positives, privacy, attribution, and effort. Here is the short version.

Is Harev a security product?

No. Harev is a revenue recovery product. The goal is to identify monetizable sharing patterns and convert them into paid seats before you ever think about restrictive enforcement.

How is this different from FingerprintJS or auth tooling?

Fingerprinting and auth tools can tell you something about identity or sessions. Harev is the monetization layer on top: it scores sharing patterns, decides when confidence is high enough, and presents a native upgrade path tied to recovered revenue.

Will this annoy legitimate users?

That is exactly why Harev is built around confidence and escalation. Most accounts begin in observation mode. Recovery should happen through upgrade prompts before anything restrictive is needed.

What if browsers make fingerprinting weaker over time?

Harev uses browser signals, but not only browser signals. Behavioral, concurrency, geo-distance, and server-side usage signals are a core part of the decision, so the system does not depend on any single fingerprinting method.

How does the revshare model work?

Founding-cohort customers pay nothing upfront. Harev only earns 10–15% of revenue recovered from Harev-attributed upgrade flows, measured against your baseline and agreed with you during onboarding.

How long until we see meaningful signal?

The exact timeline depends on traffic and usage density, but the early rollout is designed to surface signal quickly and calibrate thresholds with you instead of guessing from day one.

What data do you collect?

Harev focuses on lightweight device, session, and behavior signals needed to distinguish likely sharing from normal use. The goal is to make confident monetization decisions, not to collect unnecessary personal data.

Who is the best fit for early access?

The strongest fit today is web-first AI SaaS, e-learning, and premium B2B products with paid subscriptions, clear seat economics, and enough usage density to make sharing visible.

Request early access

Tell us about your product and where sharing is already leaking revenue.

If there is a real fit, we will follow up with how the founding cohort works, what your rollout could look like, and whether Harev is worth testing in your business right now.