Powerful fraud prevention tailor-made for marketplaces and communities

Drive engagement, build trust, and prevent abusive content and scams with real-time machine learning.

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95% reduction in fraud losses

Month-over-month business growth, but fraud has stayed low

“Sift Science is my one-stop shop. I don’t have to look at anything else for useful, actionable data.”
- Maritza Dominguez, Trust & Safety at Patreon

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One sophisticated platform prevents all fraud and abuse

Whether you're wrestling with fake listings, malicious content, counterfeit goods, or scams, Sift Science can help.

Our machine learning and natural language processing technology is designed to detect bad actors of all types – before they strike.

  • Expand your user base

    Confidently remove friction for legitimate users to join and start interacting.

  • Strengthen trust and safety

    Ensure your users have an exceptional experience that builds trust in your business and encourages repeat business.

  • Prevent fraud and scams

    Stop bad actors before they damage your business' reputation – on desktop, mobile apps, and mobile browsers.

Leverage the power of machine learning

  • Marketplace- and community-focused signals

    Our technology excels at detecting buyer fraud, seller fraud, collusion, spammers, and scammers.

  • Real-time decisions

    We use natural language processing and machine learning models calculate risk scores every time a user takes action on your app, or on any app or website in our network.

  • Data from online communities worldwide

    Bolster your custom model with learnings from our global network of 12,000+ sites and apps.

  • Custom models that keep learning

    Send data unique to your business, and your machine learning model will grow increasingly accurate and effective.

Fraud prevention tailored to your marketplace or community

Our solution is fully customizable to your data and fraud detection needs. Sift Science can learn from any data you send us.

Examples of custom fields:
  • Seller rating
  • Profile completeness
  • Social engagement
  • Text analysis
View integration guide