Applied AI and machine learning

You can power a smarter future with data science and advanced analytics.

Your business faces challenges from all sides – especially when planning for a complex future.

We can help. The Crowe applied AI and machine learning team brings strategic insights, mathematical and computational know-how, and practical business solutions that when applied to your data can simplify the complexity in your business today and tomorrow.

Let's talk

We collaborate with you on your toughest business challenges. 

Some challenges can’t be solved with solutions off the shelf. We work with you to understand your needs and build solutions that are adaptive, fast, and insightful. Our solutions can help clients:

Reduce problems

Using mathematical optimization in the healthcare industry, patient wait time can be reduced by improved scheduling of procedures.
Leveraging historical machine sensor data in manufacturing, unplanned down-time can be minimized by predicting when machines require maintenance.
Demand forecasting models can increase profitability and reduce uncertainty by providing more accurate and optimal inventory estimates.

Reveal potential

Machine learning models, built on customer and purchasing data, can predict what product or services particular customers are most likely to buy next.
Applying anomaly detection algorithms to provide real-time monitoring of the prices that sales team offer clients can avoid unnecessary lost revenue.
Deep learning models can predict the likelihood of increased revenue versus a write-off, resulting in improved efficiency of your limited human resources as they prioritize what claims to investigate.

Remove tedious tasks

Computer vision and natural language processing (NLP) solutions can automatically extract data from tax forms, financial statements, and other PDFs.
Tapping into generative AI large language models can reduce time spent summarizing documents or generating narratives for clients.
Eliminate hours spent on tedious, error-prone text classification by leveraging machine learning models trained to solve this problem.

Reduce problems

Using mathematical optimization in the healthcare industry, patient wait time can be reduced by improved scheduling of procedures.
Leveraging historical machine sensor data in manufacturing, unplanned down-time can be minimized by predicting when machines require maintenance.
Demand forecasting models can increase profitability and reduce uncertainty by providing more accurate and optimal inventory estimates.

Reveal potential

Machine learning models, built on customer and purchasing data, can predict what product or services particular customers are most likely to buy next.
Applying anomaly detection algorithms to provide real-time monitoring of the prices that sales team offer clients can avoid unnecessary lost revenue.
Deep learning models can predict the likelihood of increased revenue versus a write-off, resulting in improved efficiency of your limited human resources as they prioritize what claims to investigate.

Remove tedious tasks

Computer vision and natural language processing (NLP) solutions can automatically extract data from tax forms, financial statements, and other PDFs.
Tapping into generative AI large language models can reduce time spent summarizing documents or generating narratives for clients.
Eliminate hours spent on tedious, error-prone text classification by leveraging machine learning models trained to solve this problem.

Let's talk

At our core, we’re a team of problem solvers.

Technology is moving fast. Businesses have more ways to store data and information and more opportunities to use that information to solve problems.

We can help you identify and capitalize on opportunities that couldn’t be tackled before by applying our experience and expertise.

Many of our professionals have advanced degrees in areas like applied mathematics, computer science and engineering, predictive analytics, biostatistics and informatics, and computational social science.

Let's talk

It’s not magic. It’s math.

Solving problems at a core level can feel like magic – and it’s what we do every day.

Here are just a few examples of how our team combines the tools of applied data science with business strategy:

Advanced analytics

One problem for metals companies is determining how to optimally slit supply coils into smaller demand coils to minimize costs and scrap metal. Our team advanced the functionality of the Crowe Metals Accelerator product by applying mathematical optimization algorithms to solve this problem.

Learn more about the Crowe Metals ERP Accelerator

Machine learning

The account resolution suite of products reviews 1 million transactions per day for hospital billing departments. It resolves accounts automatically and prioritizes manual work using global models that combine training data from multiple hospital systems.

See how Crowe Account Resolution AI helps healthcare systems

Artificial intelligence

In many industries, it’s important to be able to analyze contracts quickly and extract key terms and values. Using tools in NLP, we built a solution to pinpoint where the critical terms are located and extract the relevant information from the document.

Explore Crowe Contract Manager for construction

This process aggregates applied data science with business strategy.

Each of these phases yields meaningful results for you and your business.

Ideate to uncover possible solutions

Discover the path forward

Develop a new way to solve your problem

Activate and track performance

Ideate to uncover possible solutions

We help answer questions, determine if problems can be addressed with applied data science, generate ideas, and pinpoint pain points. We’ll dive into the problem and begin exploring potential solutions.

Discover the path forward

We determine if available data can solve your problems by digging into your data during a time-boxed period and potentially running it against existing or prototype models.

Develop a new way to solve your problem

We’ll work closely with you to define the right path to monitor and support a successful solution. We iteratively build your solution and prepare to deliver it, typically via an application programming interface.

Activate and track performance

We’ll release our first version of your solution, track its performance, and release updates or new features. Once we’ve validated that the performance meets your objectives, we can explore ways to replicate or scale success.

You get value every step of the way.

Every time we dig into data and build prototypes, we learn new things – and we pass those findings on to you. It’s our job to guide you through these findings and chart the smartest way forward.

You might be wondering...

What industries does the Crowe applied AI and machine learning team work in?

We’re everywhere Crowe is. If you have data, we can work with you regardless of industry. Current industries include healthcare, banking, construction, metals and manufacturing, financial services, and talent solutions.

How do I know if my problem is one that applied AI and machine learning can solve?

Talk to us! If you have data but you’re not sure whether it lends itself to an applied data science solution, we’ll work together to understand your problem and recommend solutions. If our approach isn’t right for your problem, you’ll walk away with actionable returns from your time with us, such as referrals or recommendations for data gathering and structure.

What is a typical engagement length?

It depends. We start by working closely with you to understand your problem and explore your data before developing and launching your solution. If our approach isn’t right, we’ll end our engagement rather than push a solution that’s not right for you. Whether our engagement lasts two days, two weeks, or two months, you’ll walk away from each step with valuable strategic insights.