Clearview is not the first company to automate the process of trawling publicly available information. Other intelligence platforms sold to law enforcement, including ShadowDragon’s SocialNet, Penlink’s Tangles, and Fivecast, help investigators uncover aliases and associates and map a person’s digital footprint.

Andrew Guthrie Ferguson, a George Washington University law professor who studies AI and policing, describes this kind of automated investigation as “digital rummaging.” “They’re basically going to create a profile of you based on all of the random digital clues you left on the internet,” he explains. In practice, that means gathering scattered bits of information that once lived in separate places but were difficult to connect.

Woodrow Hartzog, a Boston University privacy scholar, argues that the labor of investigative work once served as a practical check on surveillance. By vastly reducing the labor required to investigate a person, tools like InquiryIQ also eliminate those checks. “The privacy protections we have in place right now were mainly built in a world that assumed a certain amount of friction in the ability of governments to collect information about people,” he says. “There are a lot of rules we never had just because we never needed them—because there were these practical barriers to following everyone around.”

When an InquiryIQ search is finished, the interface is designed to present the officer with the identities, connections, and other details the system has surfaced, which the officer can accept or reject before they are added to the profile. Clearview warns that automatically generated demographic, social media, and arrest data “may or may not be accurate.” Before accepting any finding, the officer must attest that they independently verified it.

Kyler says that human review is central to Clearview’s design. The system is meant to surface possible leads, not determine what is true, he says. “That’s the job of an analyst—to evaluate what’s true, what’s not; what’s noise, what’s reality.”

“A human in the loop is a little bit of a cold comfort,” Hartzog says. Over time, investigators can defer to automated systems until the person checking the machine becomes “a sort of rubber stamp.”

For example, in United States v. Sant, a Minnesota case involving undercover Homeland Security Investigations agents and surveillance of political activists, defense lawyers obtained a Clearview report drawing matches from roughly 15 years of protest photography. Every result was stamped “Accepted by Guy Gino,” including one Clearview itself labeled “A Less Likely Result”—which, the report’s footnote notes, can only be exported if a user accepts it. Defense attorneys allege the report swept in photos of an entirely different man, his pregnant wife, and young daughter. (There is no evidence InquiryIQ was used in the case.)

Pitfalls and Silver Linings

In the prototype WIRED reviewed, what InquiryIQ returned could vary depending on which model was selected. Its interface includes a control for choosing the model that runs the research and lists xAI and Amazon Bedrock, a platform for accessing models built by other companies.

In 2025, what xAI said was an unauthorized change to Grok’s system prompt caused the chatbot to inject claims about a supposed “white genocide” in South Africa into unrelated conversations. Less than a month later, after another change to its instructions, Grok produced antisemitic posts and praise for Adolf Hitler. SpaceXAI did not respond to a request for comment.