Catch high-risk merchant content. Avoid fines and reputational damage.
Our AI agents monitor merchant content for violations of local regulations, card network rules and your own internal policies.
Interactive demo
See how our AI can detect content that violates compliance policies
* Results are private and viewable only by you. Data is used for analytics purposes only and never shared with third parties.
** For demo purposes, only a subset of urls from the domain will be scanned, not including images or files.
Tailored Compliance for Your Business
Automate content checks, meet card network rules, and protect your brand—whether you're a PayFac, Acquirer, Marketplace, or SaaS Platform.
E-commerce Platforms
Gain visibility into user-generated content, flag policy breaches, and maintain a safe, trustworthy environment at scale.
Payment Facilitators
Detect content violations and merchant misrepresentation during onboarding and monitoring to meet regulations and avoid fines.
Acquirers
Effectively manage portfolio risk by automating merchant website monitoring and identifying non-compliant content proactively.
SaaS Platforms
Protect platform integrity and user trust by ensuring hosted or shared content aligns with policies and regulatory standards.
How MerchantScreen Works
Compliance workflows shouldn’t rely on guesswork. Here’s how we change that.
Turn Your Policies into Automated Checks
We convert your policies and SOPs into structured AI-driven checks ready to run at scale.
Scan Merchant Content Automatically
Add your merchant URLs to the platform, manually or via API. Once added, we continuously scan them for violations.
Act on What Matters
Get focused, evidence-based alerts. Flag real risks early—without chasing false positives.
Designed for Confident Compliance
Know exactly where you stand. Get clear, actionable insights tied to the rules that matter—so you can act faster, stay aligned, and move forward with confidence.
Merchant reviews are broken. We’re building a better way.
We’re working closely with compliance teams to solve this at scale. What it could look like in your context?