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

An operational challenge A promising use case A prototype that needs direction A portfolio of AI opportunities

An engagement can deliver

Prioritized roadmap Opportunities assessed for value, feasibility, data readiness, and risk.
Working prototype A solution stakeholders can test with real workflows and data.
Path to deployment Technical direction, responsible AI practices, and knowledge transfer.

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 and AI opportunities to determine where AI can create value, what should be prioritized, and what a solution would require.

Explore AISH roadmapping ↓
02

Test a promising idea

Investigate a defined workflow or use case and create a prototype stakeholders can evaluate before committing to a larger build.

Explore FDE ↓
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.

A focused AI Solutions Hub engagement

Forward-Deployed Engineers

Forward-Deployed Engineers (FDE) is one way organizations can work with the AI Solutions Hub. It is designed for a defined workflow or use case that would benefit from focused technical discovery, scoping, or prototyping.

An AI Solutions Hub technical lead oversees the engagement, while two certified Northeastern graduate students provide hands-on technical capacity.

Ways to work with the AI Solutions Hub

Engagements do not have to follow every stage. We start with the level of support your opportunity requires.

01

Roadmap + scope

Identify valuable AI opportunities, prioritize where to focus, and define what a solution would require.

02

FDE: Test + prototype

Investigate a defined workflow, test feasibility, and validate an approach before a larger build.

Forward-Deployed Engineers
03

Build + deploy

Engineer and integrate custom AI solutions intended to operate in your organization's real environment.

Within an FDE engagement

Match the work to what you need to learn.

FDE engagements can focus on investigating a defined opportunity, developing its requirements, or creating a prototype that your team can test.

01 · Investigate

Understand the opportunity

Examine a defined workflow or use case, including its users, current process, available data, pain points, dependencies, and technical considerations.

Output: A clearer definition of the opportunity and recommended next step.

02 · Scope

Define what a solution requires

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

Output: An actionable requirements document and recommended technical approach.

03 · Prototype

Test the proposed approach

Create a working demonstration your team can use to test the concept and gather feedback 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 a defined workflow that involves repetitive work, information spread across multiple sources, or significant manual research and review.

  • 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
Is FDE the right fit?

Choosing an AISH engagement

Start at the level your opportunity requires.

FDE may be a good fit when:

  • You have a defined workflow or operational challenge worth investigating.
  • You want to clarify requirements or test feasibility before funding a larger build.
  • You can provide process knowledge and representative information or sample data.
  • Your team can participate in regular check-ins and provide feedback.

A full AISH build may be better when:

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

What FDE is: A paid, scoped business engagement led by the AI Solutions Hub. It is not an internship or student placement. FDE prototypes are designed to test an idea and inform next steps, not serve as production-ready applications.

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

Talk with our team

The team behind the work

The right expertise for the problem.

AI challenges rarely fit neatly into one discipline. The AI Solutions Hub can bring together the people, technical capabilities, and domain knowledge each engagement requires.

Omer Alis, Director of the AI Solutions Hub
AI Solutions Hub leadership

Omer Alis

Director, AI Solutions Hub

Omer leads the AI Solutions Hub, connecting organizations with the technical expertise, research capabilities, and talent needed to move AI initiatives forward.

Talk with our team
Northeastern network

Built around your challenge, not a fixed bench.

Each engagement can draw on expertise from across Northeastern. That means we can assemble a team around the technical problem, industry context, research needs, and stage of the work rather than limiting the engagement to a fixed group of specialists.

01 Applied AI professionals

AI engineers, data scientists, software developers, and technical delivery expertise.

02 Faculty + researchers

Specialized expertise from across Northeastern's research and academic network.

03 Graduate + co-op talent

Emerging technical talent that can extend capacity and contribute directly to applied work.

04 Domain expertise

Relevant knowledge across industries, disciplines, and specialized problem areas.

Preview of the AI Solutions Hub overview

Take a closer look

Explore the AI Solutions Hub.

See how Northeastern works with organizations to identify AI opportunities, build and test custom solutions, and move promising work toward real-world deployment.

View the overview

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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