Generative AI and AI/ML

ML/AI solutions on AWS Cloud

Generative AI Solutions that Generate Meaningful Results

Shaped by generative AI engagements with current customers, our services are purpose-built to help organizations embrace generative AI with confidence.

NorthBay Generative AI Success Stories

Experience enabling a variety of AI/ML use cases in multiple industries, including:

Optimizing Talent Acquisition

NorthBay, along with AWS ProServe, is currently working with a government entity in a Middle Eastern country to match candidate profiles with a database of job descriptions based on existing skills, propensity to learn new skills, and emotional intelligence. By helping them leverage AI tool sets to parse unstructured data from resumes/CVs and job descriptions into structured data and optimize the matching, the country will be able to optimize leadership decision-making while providing greater economic opportunities for its citizens.

Enhancing New Product Development

NorthBay is helping a large financial services organization be first to market with new product features by enabling them to create a minimum viable product (MVP) in 60 days. We are integrating the LLM and tool sets and semantic search to parse key data points from millions of documents, including summarization and contextual-dependent word extraction from multiple sources.

Enabling Proactive Fleet Troubleshooting

NorthBay is helping a heavy construction equipment asset management organization identify ways to leverage AI to mine information from a large number of unstructured machine manuals in order to summarize and recommend proactive maintenance, troubleshooting, and more.

Content Moderation

NorthBay is working with a Middle Eastern government agency that would like to enhance the country’s content moderation platform. By analyzing unstructured text published from foreign media/sources, images, and video content, the country leaders can better moderate content available to their constituents using Rekognition moderation.

Injury Prevention for Athletes

Athletes at a major university wear IoT devices, which collect and track body movements. Detailed metrics, video and other interactive tools, all connected to the cloud, will produce massive amounts of data. NorthBay will develop and train models that analyze and mine the data for insights that physicians and other leaders will use to predict and prevent injuries.

Diagnosis Accuracy for Patients

An early-stage health tech company was using IoT sensors to collect data from patients with implanted cardiac pacemakers. The data was then transmitted to the cloud and used to diagnose health conditions such as hypertension, heart arrhythmia, atrial fibrillation, heart attacks, etc. However, the company’s existing models only delivered 50% accuracy in the analysis and classification of the data. By partnering with NorthBay to develop a new data lake that enabled them to more broadly experiment with ML and model training, they increased the accuracy of their IoT data to 95%.

ML/AI solutions on AWS Cloud

Additional AI/ML Solutions on AWS

NorthBay helps organizations understand where, when, and how to leverage the power of AI/ML to enhance data-driven decision-making, increase productivity, and solve old problems in new ways.

We work side-by-side with our customers to ensure success at every stage of the AI/ML adoption journey by:

  • Accelerating deployment and modernizing the underlying data layer
  • Removing risks associated with achieving intended outcomes…on time
  • Gaining access to more data sources and providing flexibility to future data sets
  • Providing access to and enabling more personas in stakeholder community, while increasing overall security
  • Supplementing and complementing analytics, data science, and AI/ML expertise
  • Solving today’s challenges with a budget-friendly cost model that can scale for the future

ML/AI solutions on AWS Cloud

Generative AI and AI/ML

ML/AI solutions on AWS Cloud

ML/AI solutions on AWS Cloud

Why Choose NorthBay for AI/ML Solutions on AWS

Experience enabling a variety of AI/ML use cases in multiple industries, including:

Financial Services

  • Customer segmentation and product recommendation optimization
  • Customer lifetime value prediction
  • Investor digital behavior analysis and investment product research and development insights

Education

  • At-risk student dropout identification and intervention
  • Learning intervention
  • Learning pattern identification

Insurance

  • Claims automation
  • Forecasting and premium pricing optimization

Healthcare

  • IoT device data correlation and diagnosis classification
  • Research institutions rapid experimentation and model optimization
  • Staff and equipment resource forecasting and allocation

Manufacturing and Logistics

  • Equipment proactive maintenance, downtime avoidance, and OEE optimization

Retail

  • Consumer price optimization
  • Optimized product recommendations

Financial Services

  • Customer segmentation and product recommendation optimization
  • Customer lifetime value prediction
  • Investor digital behavior analysis and investment product research and development insights

Education

  • At-risk student dropout identification and intervention
  • Learning intervention
  • Learning pattern identification

Insurance

  • Claims automation
  • Forecasting and premium pricing optimization

Healthcare

  • IoT device data correlation and diagnosis classification
  • Research institutions rapid experimentation and model optimization
  • Staff and equipment resource forecasting and allocation

Manufacturing and Logistics

  • Equipment proactive maintenance, downtime avoidance, and OEE optimization

Retail

  • Consumer price optimization
  • Optimized product recommendations

The Power of AI/ML at Work

Experience enabling a variety of AI/ML use cases in multiple industries, including:

Injury Prevention for Athletes

Athletes at a major university will wear IoT devices, which collect and track body movements. Detailed metrics, video and other interactive tools, all connected to the cloud, will produce massive amounts of data. NorthBay will help data scientists to develop and train models that analyze and mine the data for insights that physicians and other leaders will use to predict and prevent injuries.

Expertise across AI/ML-enabling technologies

Many organizations want to immediately experiment with new models and test new ideas using their data, but are held back by the rigidity of their existing data warehouse. By leveraging NorthBay solutions such as data lake and analytics, customers can spin up an agile, scalable environment that enables experimentation and innovation with modern analytics tools.

Diagnosis Accuracy for Patients

An early-stage health tech company was using IoT sensors to collect data from patients with implanted cardiac pacemakers. The data was then transmitted to the cloud and used to diagnose health conditions such as hypertension, heart arrhythmia, atrial fibrillation, heart attacks, etc. However, the company’s existing models only delivered 50% accuracy in the analysis and classification of the data. By partnering with NorthBay to develop a new data lake that enabled them to more broadly experiment with ML and model training, they increased the accuracy of their IoT data to 95%.

Partnership across the complete AI/ML Lifecycle

NorthBay plans, builds, deploys, and even manages AWS AI/ML-based use cases for many customers. We also leverage tools such as Amazon SageMaker to automate and standardize MLOps practices, which applies DevOps practices to ML workloads in order to streamline model delivery across the machine learning development lifecycle. Because MLOps provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment, it enables use of AI/ML for true business transformation.

Injury Prevention for Athletes

Athletes at a major university wear IoT devices, which collect and track body movements. Detailed metrics, video and other interactive tools, all connected to the cloud, will produce massive amounts of data. NorthBay will develop and train models that analyze and mine the data for insights that physicians and other leaders will use to predict and prevent injuries.

Diagnosis Accuracy for Patients

An early-stage health tech company was using IoT sensors to collect data from patients with implanted cardiac pacemakers. The data was then transmitted to the cloud and used to diagnose health conditions such as hypertension, heart arrhythmia, atrial fibrillation, heart attacks, etc. However, the company’s existing models only delivered 50% accuracy in the analysis and classification of the data. By partnering with NorthBay to develop a new data lake that enabled them to more broadly experiment with ML and model training, they increased the accuracy of their IoT data to 95%.

AWS for AI/ML Use Cases

Frameworks and Services

Our Expertise

Generative AI and AI/ML

AWS SageMaker

Generative AI and AI/ML

AWS SageMaker Ground Truth

Generative AI and AI/ML

AWS SageMaker Neo

Generative AI and AI/ML

AWS Augmented AI

Generative AI and AI/ML

AWS CodeBuild

Generative AI and AI/ML

AWS CodeBuild

Generative AI and AI/ML

AWS CodeCommit

Generative AI and AI/ML

AWS CodeDeploy

Generative AI and AI/ML

AWS CodePipeline

Generative AI and AI/ML

AWS CodeStar

Generative AI and AI/ML

AWS Command Line Interface

Generative AI and AI/ML

AWS Cloud Development Kit

Generative AI and AI/ML

AWS Tools SDKs

Generative AI and AI/ML

AWS XRay