AI Solutions Hub

Move from AI ideas to working solutions.

Northeastern University helps organizations identify valuable AI opportunities, build and test custom solutions, and prepare them for real-world deployment.

Talk with our team See our work

Bring us

  • 01An operational challenge
  • 02A promising use case
  • 03A prototype that needs direction
  • 04A portfolio of AI opportunities

Engagement outcomes

What an engagement can deliver.

01 Prioritized roadmap Clear opportunities assessed for value, feasibility, data readiness, and risk.

02 Working prototype A solution stakeholders can test with real workflows and data.

03 Path to deployment Technical direction, responsible AI practices, and knowledge transfer for what comes next.

Choose your starting point

Where does your organization need AI support?

Start with the need that matters most. We shape the technical approach and engagement around your goals, data, constraints, and internal capabilities.

01

Find the right opportunity

Assess business challenges, available data, feasibility, potential value, and risk before committing to a build.

Explore FDE discovery ↓
02

Test a promising idea

Turn a priority use case into a proof of concept or working prototype that stakeholders can evaluate.

Explore FDE prototyping ↓
03

Build and deploy a custom solution

Design and develop an AI application around your workflows, users, data, security requirements, and technology environment.

See what we build ↓
04

Move an existing prototype toward production

Strengthen an existing prototype through engineering, integration, testing, deployment planning, and MLOps.

See how we work ↓
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What we deliver

AI built around real work.

We combine applied AI, data engineering, software development, and responsible AI practices to create solutions your organization can use and sustain.

01

Knowledge and document intelligence

Extract, classify, summarize, search, and reason across contracts, reports, policies, transcripts, and other unstructured information.

02

Prediction and decision support

Use historical and real-time data to forecast demand, assess risk, prioritize work, and support better operational decisions.

03

Workflow automation

Reduce repetitive work with AI-enabled intake, routing, grading, scheduling, reporting, and human-in-the-loop review.

04

Custom AI applications

Build secure assistants, conversational interfaces, analytical tools, and full-stack applications designed for your organization.

Why Northeastern

Research depth. Practical delivery.

The AI Solutions Hub brings together applied AI professionals, faculty, researchers, graduate students, and co-op talent to help organizations move from complex AI challenges to solutions that can be tested, deployed, and sustained.

01

State-of-the-art expertise

Draw on expertise across generative AI, natural language processing, computer vision, machine learning, data engineering, and responsible AI.

02

An integrated team of builders

Work collaboratively with experienced AI professionals, researchers, faculty, and emerging technical talent aligned around your organization’s challenge.

03

From research to production

Apply research-backed methods in practical settings, with the engineering, deployment planning, and knowledge transfer needed to move beyond experimentation.

Talk with our team

Applied AI in action

Solutions measured in operational impact.

Representative work across real estate, infrastructure, healthcare, finance, manufacturing, professional services, and the public sector.

Self-Serve Analytics

Automated portfolio reporting

Built for a property management organization overseeing approximately 30,000 housing units and adaptable to complex reporting workflows across industries.

Explore the solution → Bangor Savings Bank case study

Financial services

Bangor Savings Bank

An experiential approach brought AI strategy, workforce learning, and applied projects together to help the community bank build capability and better serve its customers.

Read the case study ↗ Fullscope RMS case study

Insurance

Fullscope RMS

A data roadmap, value-driven AI solutions, and workforce training helped the insurance partner create a clearer path toward sustained data and AI capability.

Read the case study ↗ Radiolife case study

Healthcare and life sciences

Radiolife

The AI Solutions Hub helped Radiolife validate a clinical-grade AI diagnostic platform for rapid infectious-disease detection.

Read the case study ↗ Inrupt case study

Technology and data

Inrupt

Northeastern and Inrupt explored how organizations can responsibly use personal data for valuable AI applications while users retain ownership and control.

Read the case study ↗ International high-tech manufacturer case study

Manufacturing

International high-tech manufacturer

Northeastern helped the organization build a five-year digital-transformation roadmap connecting strategy, data, technology, and workforce priorities.

Read the case study ↗
Explore all case studies

How we work

A clear path from challenge to capability.

You work with one integrated team throughout the engagement, with practical checkpoints and knowledge transfer built into delivery.

  1. 01

    Discover

    Define the challenge, users, desired outcomes, data, constraints, and measures of success.

  2. 02

    Design

    Assess feasibility and create the technical, responsible AI, and delivery approach.

  3. 03

    Build

    Develop and test iteratively with regular input from your team and end users.

  4. 04

    Deploy

    Prepare the solution for your infrastructure, integrations, governance, and security needs.

  5. 05

    Sustain

    Transfer knowledge and equip your team to maintain, use, and extend the work.

Forward-Deployed Engineers

Scope and test an AI workflow before committing to a full build.

Forward-Deployed Engineers is a scoped, paid business engagement that helps your organization investigate an AI opportunity, define what a solution would require, and test the idea before making a larger investment.

An AI Solutions Hub technical lead owns the scope, milestones, and delivery, while two certified Northeastern graduate students provide hands-on technical capacity.

Choose your starting point

Three focused workstreams.

Each workstream can stand alone or build toward the next.

01 · 4 WEEKS

Discover and prioritize

Examine how work gets done and identify AI opportunities based on potential value, complexity, available data, and risk.

Output: A prioritized list of AI-enabled workflows

02 · 4–6 WEEKS

Scope the workflow

Define the users, requirements, data, dependencies, risks, and technical feasibility for a selected workflow.

Output: An actionable requirements document and recommended path forward

03 · 6–8 WEEKS

Scope and prototype

Create a working demonstration your team can test before deciding whether to invest in full development.

Output: A testable, non-production prototype

What could an FDE team tackle?

Example workflows

Look for work that could become faster and more repeatable.

A strong FDE opportunity often begins with work your team performs repeatedly, information spread across multiple sources, or a decision that requires significant manual research.

  • Research, matching, and qualification workflows
  • Industry-specific AI assistants and agents
  • Contract and document intelligence
  • Data synchronization and transition workflows
  • Reporting and dashboard workflows
  • Ticket, claim, or intake triage
  • Internal knowledge search and summarization
  • Sales follow-up and CRM workflows
Who works with your organization?

Your engagement team

Clear roles and one point of accountability.

Technical oversight

AI Solutions Hub technical lead

Owns the scope, milestones, technical direction, and overall delivery.

Applied technical capacity

Two Forward-Deployed Engineers

Certified Northeastern graduate students who investigate, scope, and prototype alongside your team.

Organizational expertise

Your team

Provides process knowledge, representative information or sample data, and feedback through weekly check-ins.

Is FDE the right fit?

Choosing an engagement

Start at the level your opportunity requires.

FDE is a good fit when:

  • You have a workflow or operational challenge to investigate.
  • You want to define requirements or test feasibility before funding a larger build.
  • You can provide process knowledge or representative sample data.
  • A team member can participate in weekly check-ins and provide feedback.

A full AI Solutions Hub build may be better when:

  • The solution must connect to live production systems.
  • It will use sensitive or production data requiring significant security and governance controls.
  • You need a production-ready application rather than an early prototype.
  • The work requires extensive integrations, deployment engineering, or ongoing technical ownership.

Is this an internship or student placement?

No. FDE is a paid, scoped business engagement built around an organizational need and defined deliverable.

Who are the FDEs?

They are current Northeastern graduate students with relevant technical backgrounds who have completed a dedicated certification program.

Is the prototype production-ready?

No. It is designed to test the concept and help your organization decide whether to pursue a full build.

What determines scope and cost?

Scope depends on the workstream, data availability, technical complexity, integrations, security needs, and intended outcome.

Not sure where to begin? We can help determine whether discovery, scoping, prototyping, or a full build is the right next step.

Discuss an FDE engagement
Omer Alis, Director of the AI Solutions Hub Applied AI leadership

Meet the expert

Omer Alis

Director, AI Solutions Hub

Omer leads a multidisciplinary team of AI experts, data scientists, and data engineers. Working with students, faculty, and researchers, the team helps organizations turn AI strategy, data opportunities, and emerging technologies into practical solutions that can be tested, deployed, and scaled.

Preview of AI Solutions Hub 2025 PDF

Download the AI Solutions Hub 2-Pager

Explore how Northeastern University’s Institute for Experiential AI helps organizations move from experimentation to production with real-world AI solutions that deliver measurable impact.

Download PDF

How can the AI Solutions Hub help you?

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Meet Our AI Solutions Hub Team

Omer Alis
Director, AI Solutions Hub

o.alis@northeastern.edu

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Akhil Chitreddy
Data Engineer

a.chitreddy@northeastern.edu

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Esenia (Kseniia) Mavlikhanova
Project Manager

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Ashmit Gupta
Data Scientist

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Jay Vipin Jajoo
Data Scientist

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Pavanchytanya Dharmapuri
Data Scientist

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Shivram Nekkanti
Data Scientist

s.nekkanti@northeastern.edu

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Kahan Dhaneshbhai Sheth
Data Scientist

sheth.kah@northeastern.edu

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Jithin Veeragandham
Data Scientist

veeragandham.j@northeastern.edu

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Reena Sajad Hyder
Data Scientist

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Sean Martin
Business Development Manager

se.martin@northeastern.edu

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Vignesh Ramaswamy Balasundaram
Data Scientist

ramaswamybalasunda.v@northeastern.edu

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