Beyond the shift

Lori Kaye Lodes

Contributor

November 2, 2026

NORTHEAST WISCONSIN – Nearly five years of workforce data. Tens of thousands of completed shifts. More than 110 variables that influence whether a worker will show up, perform, and deliver.

Behind Croux – the artificial intelligence-powered staffing platform gaining traction in Northeast Wisconsin and beyond, as first covered in the Aug. 11, 2025 issue of The Business News – is a predictive engine that has spent nearly five years learning something crucial: what makes people reliable.

That growing knowledge may be just as valuable as the technology itself, Jennifer Ryan, CEO and Co-Founder of Croux, said.

Ryan said what began as a platform connecting hospitality businesses with flexible workers has grown into something much bigger, and has helped shape Croux’s original mission: connecting businesses needing dependable workers with people seeking flexibility in how and when they work.

Today, Croux is using nearly five years of workforce data to predict reliability, account for the different needs of businesses and markets, and identify workers who might otherwise be overlooked, Ryan said.

She added that the Birmingham, Ala.-based company is now putting its data to work in new ways.

With an expanding presence in markets including Northeast Wisconsin, Ryan said Croux is expanding how it can simplify workforce management and making inroads in manufacturing.

For Ryan, she said those developments are about more than expanding Croux’s reach; they’re about using what the company has learned to connect the right people with the right work at the right time.

“Our insights come from nearly five years of learning how people actually show up for work; what they prefer, what keeps them coming back, and what makes them reliable.”

Whereas traditional staffing agencies typically focus on volume (finding more workers to fill more positions), Ryan said Croux focuses on which workers are most likely to show up and perform.

“We track 113 reliability signals, from punctuality and uniform alignment to ratings from the business and co-workers,” she said. “Those are the things a person can control, and they say far more about someone’s potential than a resume does.”

Gender, race, age, education, and economic status never enter Croux’s model, Ryan said.

Instead, she said it looks only at what a person controls, “so everyone who wants a shot gets a fair one.”

By analyzing those reliability signals and drawing on nearly five years of workforce data, Ryan said Croux aims to predict which workers are most likely to succeed in a particular assignment.

Croux’s performance, she said, provides evidence that it’s working: it delivers shift fill rates of approximately 90%, no-show rates below two percent, and an average shift fill time of four hours.

“Reliability is what we’ve been able to learn from and measure for nearly five years,” Ryan said. “Traditional staffing was never built to track it.”

That growing collection of information is also something she said a new competitor can’t immediately replicate simply by introducing its own AI staffing platform.

Ryan said the years of worker behavior and completed assignments behind Croux’s matching engine are what help set it apart.

It also benefits workers, she noted; for example, a worker without a college degree or conventional employment history may still demonstrate exceptional reliability.

Ryan said traditional employment schedules can leave many people on the sidelines, including parents managing childcare, people approaching retirement, those seeking extra income, and individuals returning to work after an extended absence.

With Croux, she said the goal is to connect those workers with opportunities and employers that fit their availability and abilities.

“What matters is what you can control: showing up on time, in uniform, and being able to do the job you signed up for,” Ryan said. “Availability and abilities versus resumes.”

For employers, she said the goal is greater confidence that workers will show up and perform.

For workers, it creates opportunities to build a reputation through their performance, Ryan said, rather than relying solely on traditional credentials.

She added that the data also helps Croux adjust its approach for different businesses and communities.

Historically, Ryan said, staffing agencies relied heavily on local knowledge.

In this model, she said a staffing representative might know which workers were dependable, which businesses had unusual needs, and how a particular community operated – but that approach was difficult to expand across many markets.

Ryan said Croux’s technology is designed to recognize those differences while serving businesses across multiple locations.

“Our machine was built to bend,” she said. “Local agencies have always understood the nuance of their communities, but that knowledge lives with a few people and is hard to scale. Gig platforms scale by flattening every job into the same thing. We built Croux’s AI engine to embrace the nuance, so businesses get the high-touch, high-trust experience of a local partner with the scale, speed, and resources of a national platform.”

Ryan said such flexibility allows the platform to adjust to different industries and employers rather than treating every staffing request the same way.

“We don’t treat the manufacturing plant the same as the hotel down the street even though similar talent may work shifts at both.”

Further, she said this ability to adapt is becoming increasingly important as Croux moves beyond its original markets and hospitality roots.

Making sophisticated technology remarkably simple

Ryan said Croux is putting its growing collection of workforce data to work in a way that makes staffing easier for managers with the introduction of Croux Concierge.

Per croux.co, Croux Concierge – launched over the summer – is a conversational AI tool that allows managers to describe their staffing needs in everyday language.

Instead of navigating scheduling systems, completing forms, or contacting multiple agencies, with Croux Concierge, Ryan said a manager can simply ask for what is needed.

For example, a hospitality manager preparing for a Saturday event could request 10 bartenders or upload a banquet event order and ask Croux to develop a staffing plan.

Ryan said Croux’s AI engine reviews the request against available workers, previous performance, staffing ratios, budgets, and other requirements, then prepares a recommendation for the manager to review.

“Ask for what you need in plain language, and it gets done – there are no forms to fill out.”

The simplicity of that experience depends on the technology operating behind it, Ryan said.

“The magic happens behind the scenes: a complex engine works nonstop so the experience feels fast and simple for the people using it.”

Ryan said one of the biggest benefits may be reducing the time hospitality managers spend planning staffing for events.

A large wedding, for example, may involve a banquet event order spanning dozens or even 100 pages, with details ranging from table arrangements and menus to service schedules and staffing requirements.

Turning that information into a workable schedule, Ryan said, can take four to 10 hours for a single event, as managers determine how many employees are needed, when they should arrive, which workers are available, and how staffing costs fit the budget.

In contrast, she said Croux Concierge can review the information and generate a proposed staffing plan in approximately 30 seconds.

Ryan said that time savings can give managers more opportunities to work directly with employees and guests rather than spending hours on administrative tasks.

She said Croux designed Concierge to reduce repetitive work while keeping managers involved in staffing decisions – adding the technology can also help managers review worker performance, identify preferred employees, and obtain labor reports without navigating several systems.

And, unlike a general-purpose chatbot, Ryan said Concierge draws on a key differentiator: Croux’s workforce data, including staffing ratios, pay expectations, worker performance, and the needs of individual businesses.

She said this depth of information is what allows the company to offer a seemingly simple experience built on years of sophisticated development and data collection.

“The simpler [a tool] is on the front end, the more work [that’s been] done on the back end.”

Manufacturing pilot opens a new frontier

Ryan said nearly five years of collecting and studying workforce data are now paying off in a whole new industry: manufacturing.

In Northeast Wisconsin, she said, Croux has spent approximately 18 months testing its technology with a large manufacturer.

Ryan said the pilot has been successful enough that the manufacturer has signed a second-year contract.

The initiative is testing whether the same reliability measures used to match hospitality workers can help fill positions in manufacturing, she said – an industry where traditional first-, second-, and third-shift schedules have long been the norm.

While those schedules support production needs, Ryan said these options can exclude people who are willing and able to work but cannot commit to conventional hours.

She said Croux approached the manufacturer with a different idea: could the company offer more flexible scheduling while still meeting its production goals?

The resulting pilot, Ryan said, focused on essential assignments that did not require specialized schooling or extensive experience.

Rather than looking only for people with manufacturing backgrounds, she said Croux identified workers with strong reliability histories and high Trust Scores in the tool, including individuals who might never have considered manufacturing jobs.

“We said, ‘Let’s see if people with no manufacturing experience – but a strong track record of reliability – can support you,’” Ryan said. “The answer is a resounding ‘yes.’”

She said the pilot allowed the manufacturer to try more flexible scheduling while continuing to focus on production, customer orders, labor costs, and employees receiving their desired hours.

Further, Ryan noted that it revealed a group of potential workers who had been overlooked.

“They were missing out on an enormous population of people who wanted to work, but traditional shifts didn’t fit their lives.”

By matching workers with assignments that fit their availability, Ryan said Croux helped the manufacturer reach people who might not have responded to traditional job postings.

She said the experience also showed that scheduling flexibility and reliability do not necessarily have to compete.

“We brought flexibility into a very traditional way of working and connected [businesses] with a whole community of people who never would have answered their job postings.”

For Northeast Wisconsin manufacturers, Ryan said the pilot suggests another way to address workforce shortages: rather than focusing exclusively on recruiting more people, businesses may be able to reach additional workers by reconsidering how jobs are scheduled.

Growth beyond hospitality and beyond Wisconsin

The technology isn’t the only thing growing at Croux, Ryan said – so is the company’s footprint.

Nearly five years after getting its start in Birmingham, Croux now operates in seven markets across the Southeast and Midwest.

In June, the company announced its expansion into Auburn, Mobile, Tuscaloosa, and Montgomery, Ala., along with Green Bay and Kohler, Wis.

Per its website, Croux’s clients include businesses associated with major hospitality brands such as Marriott, Hyatt, and Wyndham, along with NFL-related operations.

The company reports working with approximately 100 business partners, 50,000 registered workers, and 55,000 completed shifts.

And yet, Croux has accomplished that with a team of six employees, Ryan said.

She credited AI-driven automation with allowing the company to grow without adding administrative staff at the same rate.

“We’ve filled nearly 60,000 shifts with a team of six,” she said. “Staffing agencies typically have to scale headcount with revenue. We don’t, and that keeps costs down for our business partners.”

Ryan said Croux uses AI for everything from onboarding and matching workers to customer service and fraud prevention.

She added that AI can also help people who may feel uncertain about returning to work or accepting an unfamiliar assignment.

“Someone coming back to work after years away or entering a new market has real questions: ‘Am I prepared? Do I need skills I don’t have? Can I work with a friend? How will I know I’m doing a good job?’” Ryan said. “Our responsibility is to answer those before the first shift.”

She said Croux can use AI to answer routine questions and guide workers through onboarding, while its human team provides personal support when needed.

Its AI customer support agent, Sam, handles approximately 98% of routine inquiries, Ryan said, allowing the company’s small team to focus on situations requiring more personal attention.

She said the company intentionally keeps people involved in its operations, particularly when situations require judgment, encouragement, or individual attention.

“AI handles the high-volume questions so our team can show up where a human matters most, like providing a pep talk before someone’s first shift in eight years, to celebrating another person’s 100th.”

Ryan said this efficiency also helps Croux manage costs for businesses while supporting competitive wages.

For basic assignments that do not require specialized skills, she said typical wages through the platform range from approximately one and one-half to two times the applicable minimum wage.

Beyond geographic growth, Ryan sees opportunities to bring Croux into additional industries.

Construction, she said, is particularly high on the list.

Like manufacturing and hospitality, construction depends on reliable workers, but Ryan noted staffing needs can change with project schedules, weather, specialized trades, and the availability of support labor.

She said she regularly hears from construction businesses seeking workers, from skilled tradespeople to individuals capable of handling essential support tasks.

Yet Ryan said she believes the same approach used to predict whether a banquet server will complete an assignment successfully can help businesses identify dependable workers in manufacturing, construction, and other industries.

The work may differ, but the need for reliable people remains the same, Ryan said.

The company operates in what she said she calls the physical economy – industries such as hospitality, manufacturing, and construction, where people are still needed to get the work done.

“Walk any plant floor, any hotel grounds, any construction site – robots aren’t doing the work; people are.”