Data and dashboards
Analysis, visualization, KPI summaries, forecasting, Power BI dashboards, and decision-support tools.
Talent across the network
Build the team around the project.
Working Labs connects organizations with graduate talent, faculty guidance, and academic programs from across Northeastern University. These campus profiles highlight concentrations of programs and industry connections, but partners are not limited by location. We match talent from across the network to the skills each project requires.
Boston connects Working Lab projects with graduate talent and faculty spanning technical, business, research, and health-related disciplines.
Relevant advertised graduate programs
- Artificial Intelligence, Applied AI, Computer Science, and Data Science
- Analytics, Data Analytics Engineering, and Information Systems
- Biotechnology, Bioinformatics, and Health Informatics
- Business Analytics, Project Management, Robotics, and engineering programs
Example project directions
- Data analysis and decision-support tools
- Software and workflow prototypes
- Health and life-sciences research
- Business, product, and technology evaluation
The Roux Institute connects organizations with applied graduate talent, faculty, and technical experts in an ecosystem built around employer projects.
Relevant advertised graduate programs
- Artificial Intelligence, Align Artificial Intelligence, and Applied AI
- Computer Science, Data Science, Analytics, and Information Systems
- Biotechnology, Bioinformatics, and related graduate certificates
- Project Management
Example project directions
- Forecasting, dashboards, and predictive tools
- AI workflow exploration and prototypes
- Software and internal applications
- Operations, product, and market research
Arlington connects projects with graduate talent and expertise relevant to the National Capital Region’s technology, public-sector, security, and mission-driven organizations.
Relevant advertised graduate programs
- Applied AI, Analytics, Computer Science, and Information Systems
- Cybersecurity and Software Engineering Systems
- National Security and Intelligence, Public Policy, and Urban Informatics
- Project Management and Engineering Leadership and AI Fundamentals
Example project directions
- Secure workflow and data analysis
- Technology and policy research
- Cybersecurity process improvement
- Mission-focused software concepts
Oakland and Silicon Valley contribute different, complementary program strengths across the Bay Area. Teams can draw from either campus or combine talent from across the Northeastern University network.
Relevant advertised graduate programs
- Silicon Valley: Artificial Intelligence, Computer Science, Data Science, Analytics, Information Systems, and Project Management
- Oakland: Analytics, Business Analytics, Bioinformatics, Biotechnology, and Information Systems
- Oakland: Semiconductor Engineering, Public Administration, Public Policy, and Sustainability and Climate Change Policy
Example project directions
- AI, analytics, and software concepts
- Biotechnology and bioinformatics research
- Business, market, and information-systems analysis
- Semiconductor, public-policy, and sustainability projects
Toronto connects organizations with graduate talent and programs relevant to technology-driven industries, including financial services and life sciences.
Relevant advertised graduate programs
- Applied AI, Analytics, Informatics, and Information Systems
- Data Architecture and Management and Software Engineering Systems
- Bioinformatics, Biotechnology, and Regulatory Affairs
- Applied Logistics and Project Management
Example project directions
- Financial and operational analytics
- AI workflow, data architecture, and software projects
- Biotechnology, bioinformatics, and regulatory research
- Logistics, project planning, and process improvement
Seattle contributes graduate talent in computing, data, engineering, intelligent systems, economics, and project delivery.
Relevant advertised graduate programs
- Artificial Intelligence and Computer Science
- Analytics, Data Analytics Engineering, and Data Architecture and Management
- Electrical and Computer Engineering, Information Systems, and Robotics
- Economics and Project Management
Example project directions
- AI, software, and information-systems concepts
- Data analysis, architecture, and engineering
- Automation, robotics, and intelligent-systems research
- Economic analysis and technology implementation
Program examples are selected from Northeastern University’s currently advertised graduate offerings at each location. Offerings may change. Team composition depends on project fit, student availability, faculty or expert participation, and engagement timing.
How a team comes together
Built around the project.
Northeastern University draws from graduate talent, faculty, and technical expertise across the network based on the skills each project requires. For one project objective, a team might look like this.
Example team structure
Roles and academic backgrounds are matched to the project.
Sample objective
Custom AI tool for project estimating and sales
Project ManagerMS Project Management
Back-end DeveloperMS Computer Science
AI EngineerMS Artificial Intelligence
NU Faculty AdvisorStructure, oversight, and domain perspective
Connected ways to work with us
Choose the support that matches the work.
A Working Lab is one way to begin. If the need extends beyond a supported graduate project, Northeastern University can connect you with deeper applied AI development or a broader enterprise partnership.
Working Labs
Explore or test a defined project
Use a supported graduate team with faculty or expert guidance to produce tangible project outputs.
View Working Lab examples ↓AI Solutions Hub
Build or advance an AI solution
Work with applied AI engineers and experts when a custom solution needs deeper development, integration, or a path toward production.
Explore the AI Solutions Hub ↗Enterprise Accelerator
Coordinate training, talent, and applied AI
Bring customized employee learning, graduate project teams, and applied AI expertise together through one Northeastern University partnership.
Explore Enterprise Accelerator ↗Project examples
Real work, real outputs.
Working Labs have supported sustainability analysis, predictive tools, recommendation engines, customer retention applications, KPI dashboards, and demand forecasting.
Sustainability analysis tools
Students developed data tools to enhance sustainability analysis in retail and optimize return from mineral resource recovery.
Predictive decision-support tool
Built a scalable, predictive tool integrated with the local data environment to help guide decision making alongside internal subject matter experts.
AI recommendation engines
Faculty and student teams are building AI recommendation engines to improve customer service, marketing, and new product deployment. The first engine improved new product conversion 2X.
Customer retention web application
Students researched internal business requirements and designed and developed a web-based application for customer retention.
Automated KPI dashboard
Students designed and built an automated, scalable web-based dashboard to display and track identified KPIs.
Demand forecasting and operations planning
Students compared forecasting methods, evaluated product-level demand, and delivered code, forecasts, and dashboarding to support sales and brewery operations planning.
Featured case study
Allagash used real data to sharpen forecasting.
Allagash Brewing Company wanted to improve weekly sales forecasting by SKU, optimize inventory and shipping for seasonal brands, and understand which features mattered most for predicting sales.
1.6M+real-world records across depletions, shipments, inventory, and product attributes
6forecasting approaches compared before selecting best-fit methods by SKU
78weeks of forward-looking forecasts delivered for representative products
16%modeled cost savings when forecasting improvements were paired with smarter inventory and shipping logic
Students built and compared Prophet, Holt-Winters Exponential Smoothing, S-ARIMA, and naive baselines. Each SKU was assigned the method that minimized Weighted Absolute Percentage Error.
Allagash White was steadier and easier to forecast, while seasonal beers had shorter selling windows and less historical data. Seasonal SKUs improved from a 62% MAPE baseline to 44.5% WAPE in the project summary.
The team delivered Python forecasting code, a CSV of 78-week forward forecasts for 19 SKUs, and a Power BI dashboard filterable by date, state, product, and forecast versus actuals.
Weather looked like a strong predictor at first glance, but the correlation traced back to seasonality the model already captured, not weather itself. Combined with the practical limit of short-range weather forecasts, it was not usable for long-term planning. Demographic data was too static for week-to-week forecasting, and news sentiment added more noise than signal.
“The students at the Roux Institute took a specific business opportunity and provided different models to help us reach our goals. Their varying backgrounds and skills yielded several approaches, each helping us understand the opportunity in a new way, ultimately putting us in a better position to capitalize on the opportunity.” Allagash Brewing Company
Ready to start?
Have a project sitting on the someday list?
Talk to our team about your project, desired outcomes, timeline, and available budget to determine whether a Working Lab partnership is the right fit.