Yardstik haalt $30 miljoen Series B op terwijl AI de toekomst van vertrouwen in de arbeidsmarkt hervormt

Yardstik heeft $30 miljoen opgehaald in een Series B-financieringsronde terwijl het bedrijf voor arbeidsmarkttechnologie zich wil uitbreiden voorbij traditionele antecedentencontroles en een groeiende uitdaging voor werkgevers wil aanpakken: bepalen of werknemers betrouwbaar blijven nadat ze zijn aangenomen.

The round was led by Harbert Growth Partners, with participation from existing investors Rally Ventures, MissionOG, Crosslink Capital, Grotech Ventures, and Great North Ventures. The financing brings Yardstik’s total capital raised to $65 million. The company plans to use the new capital to develop additional fraud prevention and workforce monitoring capabilities, including motor vehicle report monitoring, Office of Inspector General exclusion monitoring, and automated alerts when professional licenses, insurance, or certifications expire.

The investment comes as generative AI is changing the nature of hiring fraud. Synthetic identities, fabricated credentials, deepfake interviews, and increasingly convincing fraudulent documents can make it harder for employers to establish whether applicants are who they claim to be. More importantly, a background check performed on someone’s first day provides little visibility into risks that develop months or years later.

Voorbij de eenmalige antecedentencontrole

That limitation has become central to Yardstik’s strategy.

Founded in 2020, the Minneapolis-based company has evolved from a background screening provider into what it calls a Human Trust Platform, combining fraud prevention, identity verification, background screening, credential verification, and continuous workforce monitoring.

Instead of treating verification as a single event during onboarding, the platform is designed to maintain a changing picture of workforce risk.

The distinction is important. A conventional background check can determine whether relevant records existed when the check was performed. It cannot necessarily tell an employer that a driver’s license expired three months later, that a new criminal record appeared, or that another risk signal emerged after employment began.

Yardstik’s Continuous Monitoring technology automatically enrolls screened workers in post-hire monitoring rather than relying exclusively on manually scheduled rechecks. Its current monitoring capabilities cover areas including criminal databases, sex offender registries, federal watchlists, and other records.

The Series B will allow the company to broaden this model into additional forms of credential and employment-related monitoring.

“If a license lapses the day after someone’s hired, an employer should know that day, not at the next annual review,” CEO Andrew Johnson said in the funding announcement, describing the difference as one between a photograph and a live feed.

AI inzetten om fraude te detecteren voordat de screening begint

Yardstik is also applying AI and data analysis earlier in the hiring process.

Its Detect AI technology is intended to identify signals associated with identity manipulation and fraudulent applications before an employer relies on a conventional background check.

Rather than looking only at criminal records, Detect AI analyzes identity-related risk signals involving personally identifiable information, payment activity, location, and IP data. Yardstik’s broader data infrastructure also examines signals such as device fingerprints, biometric mismatches, and inconsistencies between data points that may appear legitimate individually but become suspicious when analyzed together.

This addresses a different problem from traditional screening. A background check may accurately return information associated with an identity while still failing to determine whether the applicant actually owns that identity.

Yardstik pairs these fraud signals with identity verification that can compare biometric information against government-issued identification. The goal is to establish a stronger link between the person submitting an application, the credentials being provided, and the individual ultimately entering the workforce.

The approach reflects a broader shift in fraud detection as AI lowers the cost of producing convincing fake identities and documents. Screening systems increasingly need to evaluate patterns and inconsistencies across multiple signals rather than simply querying databases for records.

Arbeidsfraude omzetten in een continu bijgewerkt gegevensset

Another component is Fraud Insights, a live dashboard that aggregates fraud-related signals across an organization’s workforce.

The system can surface patterns such as Social Security numbers appearing across multiple applications, unusual device geography, and the locations where payment cards associated with applicants were issued. Instead of evaluating each applicant in isolation, this can expose patterns that potentially indicate coordinated or systematic fraud.

Yardstik recently made Fraud Insights and Continuous Monitoring standard capabilities for its customers rather than separate add-ons. The company says workers screened through the platform can be automatically enrolled in monitoring, reducing the need for employers to initiate repeated checks manually.

Continuous employee monitoring also introduces important compliance and privacy considerations. Yardstik operates as a Consumer Reporting Agency and says its screening processes comply with the Fair Credit Reporting Act, including requirements around transparency for individuals being monitored.

As workforce monitoring becomes more automated, those safeguards could become increasingly significant, particularly when AI-generated risk signals influence employment decisions.

Vertrouwensinfrastructuur bouwen voor AI‑agenten

Yardstik’s technology strategy also extends beyond its own application.

The company has built API-first infrastructure that allows marketplaces, hiring platforms, and HR technology providers to embed screening, identity verification, fraud prevention, and monitoring directly within their products. The funding announcement lists integrations with systems including Greenhouse, Lever, Workable, Fountain, Bullhorn, Avionte, and Paylocity.

More recently, Yardstik has added support for the Model Context Protocol (MCP), creating an interesting connection between workforce verification and the emerging agentic AI ecosystem.

Through its MCP integration for AI agents, developers can give AI systems access to Yardstik workflows for tasks such as initiating identity verification, ordering different background screening packages based on job requirements, or establishing recurring screening processes. Yardstik executes the underlying checks and compliance workflows while returning the results to the application or agent.

That could become increasingly relevant as AI agents take on larger roles in recruiting and workforce administration. If software agents are making or assisting with hiring decisions, the infrastructure allowing those agents to verify identities, credentials, and changing risk information may become another layer of the enterprise AI stack.

Wat continue arbeidsverificatie kan betekenen voor de toekomst van werk

Yardstik enters the Series B following a period of rapid expansion. The company reports 149% year-over-year revenue growth, a 98% account retention rate over the past three years, and customers across industries including gig marketplaces, healthcare, staffing, transportation, logistics, and childcare.

More consequential than the growth figures is the broader shift the technology represents. Background screening has traditionally been built around a single decision point: determining whether someone should be hired. Continuous monitoring changes that model by treating identity, credentials, and workforce risk as information that can change throughout a person’s employment.

AI could accelerate this transition in both directions. Generative tools are making it easier to fabricate resumes, credentials, documents, images, voices, and potentially entire identities at scale. At the same time, machine learning can help screening systems analyze combinations of identity, device, credential, and behavioral signals that would be difficult to evaluate manually.

Over time, this could turn workforce verification from a periodic administrative process into an always-on layer of enterprise infrastructure. Hiring platforms, staffing marketplaces, and HR systems may increasingly incorporate automated identity and credential checks directly into their workflows, while AI agents could initiate or respond to verification events without waiting for a human administrator.

That evolution also raises questions that will become harder to ignore. Employers will need to determine how much continuous monitoring is appropriate, which signals should be allowed to influence employment decisions, how workers can challenge inaccurate information, and where the line should be drawn between legitimate risk management and excessive surveillance.

The significance of Yardstik’s funding therefore extends beyond the expansion of one background screening platform. It reflects a larger question emerging as AI reshapes the labor market: if digital identities and credentials become easier to manipulate, how will organizations continuously establish trust without undermining the privacy and rights of the people they employ?