This Startup Catches Fraud at Scale

Variance develops AI agents specifically designed for risk and compliance, automating tasks like content review, fraud detection, and identity verification. These agents are deployed by large companies, including Fortune 500s and marketplaces like GoFundMe, to manage sensitive issues at an unprecedented scale.

Variance is building purpose-built AI agents for risk and compliance. We automate content review, fraud reviews, identity reviews at scale. We're powering some of the largest companies in the world's Fortune 500s marketplaces. We've been working with GoFundMe, for instance, to review all of their fundraisers at scale.

Variance maintained a stealth mode for three years because its technology serves as a 'secret weapon' for clients in the ongoing fight against fraud. Publicly detailing their methods or specific customer use cases could inadvertently provide fraudsters with information to circumvent their systems, making discretion a core part of their competitive strategy.

Variance usually deals with really sensitive data and sensitive issues. And the phrase I like to use is that we're building the systems that are often used by the bad guys, but we're building them for the good guys. So oftentimes it's really hard to market the use cases that customers are using Variance for because those issues are so sensitive. And if we were to market those then it may create more fraud. It may create more abuse.

A core technical challenge solved by Variance is integrating vast amounts of unstructured data from disparate sources. Their AI agents connect to internal customer data stores (often scattered across 5-10 systems), hundreds of global business registries, and the open web. Crucially, they can even scrape data directly from old UIs and internal dashboards originally built for human analysts, enabling comprehensive data collection for reasoning.

Usually, it's going to be a split between internal customer data. So, Variance is really good at connecting to all data sources, pooling unstructured data into our own data stores. And the second one is external data. So we do have access to over hundreds business registries across the world... and then our agents also have access to the open web... sometimes that data is going to be hidden behind a UI. So the only way that the Variance AI agents are able to sort of scoop up that data and reason over it is to be able to directly scrape from a UI that was built for a human.

Traditional fraud detection relied on a patchwork of deterministic rules, specific classifiers, and slow, inconsistent human analysts. Variance's AI agents replace this by providing a 'fully self-healing system' that can dynamically materialize features, reason over unstructured data and standard operating procedures, and rapidly adapt to new, complex fraud patterns like state-sponsored misinformation campaigns, enabling a much faster feedback loop against adversaries.

When you think of a fraud system, the most important feature of a fraud system is that it needs to evolve really rapidly and you need to have a really tight feedback feedback loop... And now you have AI agents that are able to sort of close the loop from a reliance and self-healing standpoint. They're able to materialize any features that a rules engine would be able to materialize. You don't need a classifier anymore because AI agents are able to read set of standard operating procedure and reason over an image or reason over sort of unstructured data.