Let’s identify and build out your AI use case

Your business data is unique, and so are the insights it holds. With artificial intelligence (AI) and machine learning (ML), you can use your proprietary data to set your business apart from competitors. The starting point is to identify your AI use case.

Our clients usually start seeing benefits in less than eight weeks. With expertise in medical and technology domains, our team can identify suitable use cases and their feasibility, guiding your solution from proof of concept to a fully operational product.

Our Process

How do you make data transformation work in your organization? In our experience, we've seen enterprise organizations reach greater success by following these steps that look at everything: your technology, data and processes.
1

Architectural assessment

  1. Understand your current business processes and how your current IT systems measure up to meet the business demands.
  2. Understand how your IT systems work by mapping data flows and evaluating where information is stored.
  3. Create a future plan for your systems that organizes data flow, ensures it's clean and secure, follows a unified data model, and can be accessed through an integration layer.
2

Transformation: Reach the future state architecture

  1. Collaborate with your internal technical teams or work independently to implement the infrastructure.
  2. Help create the necessary functions, APIs, data stores, and interfaces through cloud-based solutions or on-premises approaches if your organization doesn't use cloud technologies.
3

ML/AI use case development

  1. Opportunity discovery: With your data now clean and accessible, our healthcare domain experts and data scientists collaborate with your organization to uncover potential opportunities your data can provide. 
  2. Feasibility assessment: After identifying opportunities, we conduct a feasibility study to determine which ML algorithms could deliver the desired outcomes. This involves statistical analysis and can be done using real data, sample data, or data model knowledge. 
  3.  Proof of Concept (POC) development: We then create a POC to test the viability of the use case. This experiment, conducted in your environment or ours, provides a secure dashboard to review results and determine if the use case will deliver the desired outcomes. 
  4. Deployment: Once we confirm the use case's validity, we deploy it into production. This could involve insights tied to your platform, a module to build a search component for staff use, or implementing tools driven by generative AI. Our goal is to put the final piece in place and turn your vision into reality.
4

Continuous improvement

With ML/AI products, the potential for improvement is constant. 

  1. As the ML system gets more data, it learns and improves. 
  2. We'll make tweaks and enhancements to the data models based on the insights we receive. 
  3. New algorithms may become available, allowing for further improvements.
  4. We may discover additional data sets to achieve even better results.

Putting your goals first

Unlike many organizations that solely focus on technology, our team takes a different approach. We combine robust technical skills, profound industry knowledge, and a complete business perspective. Rather than jumping straight into the technology, we prioritize understanding the core business problem first.

To find out if your organization is prepared to use AI and ML strategically, ask yourself these basic questions:

  • How healthy is your data?
  • Are you having trouble making your analytics work?
  • How can you use your data to solve your business problems now and in the future?
  • Is your organization changing its business plan with AI and ML?
  • What are the patterns and trends in your data that could help your business decisions?
  • How are you planning to use analytics solutions responsibly?

Healthcare companies collect data and typically fall into the following categories:

  • You’re unsure about the quality of your data, whether it’s ‘clean’ or ‘dirty’.
  • You’re in the process of a digital transformation and there’s opportunity to assess the data architecture and prepare for the future.
  • You’ve cleaned up your data can access it through integration, but you don’t have a use case defined to use ML or AI.
  • You have a use case for ML and AI but lack a secure platform or resources to develop a proof of concept.
No matter where you are on your data journey, we can help.

Enhance your digital transformation with advanced analytics, ML and AI.

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