Applied AI and machine learning

Applied AI and machine learning

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.

We collaborate with you on your toughest business challenges

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

Reduce problems

  • Mathematical optimization in the healthcare industry can help reduce patient wait time and improve procedure scheduling.
  • Using historical machine sensor data in manufacturing can minimize unplanned downtime 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 help predict what product or services particular customers are likely to buy next.
  • Applying anomaly detection algorithms to provide real-time monitoring of the prices that sales teams offer clients can help avoid unnecessarily lost revenue.
  • Deep learning models can predict the likelihood of increased revenue versus a write-off, resulting in improved efficiency of limited personnel resources as they prioritize what claims to investigate.

Remove tedious tasks

  • Computer vision and natural language processing 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.
  • Specifically trained machine learning models can help eliminate hours spent on tedious, error-prone text classification.

Reduce problems

  • Mathematical optimization in the healthcare industry can help reduce patient wait time and improve procedure scheduling.
  • Using historical machine sensor data in manufacturing can minimize unplanned downtime 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 help predict what product or services particular customers are likely to buy next.
  • Applying anomaly detection algorithms to provide real-time monitoring of the prices that sales teams offer clients can help avoid unnecessarily lost revenue.
  • Deep learning models can predict the likelihood of increased revenue versus a write-off, resulting in improved efficiency of limited personnel resources as they prioritize what claims to investigate.

Remove tedious tasks

  • Computer vision and natural language processing 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.
  • Specifically trained machine learning models can help eliminate hours spent on tedious, error-prone text classification.

Aggregate applied data science with business strategy


Each of the following phases can yield meaningful results for your business.

Uncover possible solutions

We help answer questions, determine if problems can be addressed with applied data science, generate ideas, and explore potential solutions for specific pain points.

Discover a path forward

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

Develop new solutions

We 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

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

Uncover possible solutions

We help answer questions, determine if problems can be addressed with applied data science, generate ideas, and explore potential solutions for specific pain points.

Discover a path forward

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

Develop new solutions

We 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

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

We can answer your questions about applied AI and machine learning

In which industries does the Crowe applied AI and machine learning team work?
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 can work with you to understand your problem and recommend solutions. If our approach isn’t right for your problem, you can 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 can walk away from each step with valuable strategic insights.
How does Crowe stay up to date on AI?
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.

Drive measurable results with AI solutions

We bring AI into your organization in a way that works for you, catering to your specific needs.

Find out how

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Meet our team


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

We apply our experience and expertise to help you identify and capitalize on opportunities that couldn’t be tackled before.

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

Doug Schrock at Crowe
Doug Schrock
Managing Principal, Artificial Intelligence
Thomas Callaghan
Thomas Callaghan
Principal, Technology
Alison Bauter Engel
Alison Bauter Engel
AI Studio Operations Leader

Contact our applied AI team

Let’s start finding the potential in your data.
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