AI & Data Product Engineering for Industry Solutions - Student Consulting Project (Spring 2027)

Program Overview
Program Title AI & Data Product Engineering for Industry Solutions - Student Consulting Project (Spring 2027)
Organization University of Miami
# of Students Enrolled
0
# of Projects Running
0 Project/s Added (of 5 Projects Expected)

Program Timeline

Project Duration

Start Date: 03/15/27      End Date: 04/26/27

1 month

Collaboration Overview
About Students

Undergraduate Miami Business School students in AI Engineering work in small teams with faculty oversight and student coaches.

Students are developing capabilities in generative AI, RAG architectures, agentic workflows, model adaptation, AI governance, evaluation, and full-stack deployment. Their focus is not simply using AI tools, but engineering reliable AI products that solve defined business problems.

Student Level:   Bachelor Degree

Student Time Commitment:   Full Time

Team Structure:   3 - 6

Program Goals
Students will:
  • Translate a business problem into a buildable AI use case.
  • Design RAG, agentic, or other AI architectures appropriate to the challenge.
  • Build and evaluate a working AI product or analytical workflow.
  • Address accuracy, cost, latency, governance, privacy, and risk.
  • Document architecture, prompts, workflows, and implementation requirements.
  • Demonstrate the solution and business value to partner leadership.
Format Structure

Multiple Projects Multiple Teams

Format Title Ai & Data Product Engineering For Industry Solutions Consulting
Format Description
Partner with undergraduate Miami Business School students to design and build an AI-enabled product, workflow, or analytical system around a real business problem.

Teams work with RAG, agentic AI, lightweight fine-tuning, governance, guardrails, and full-stack delivery to move from business need to a working, auditable solution. Projects should have a clear user, measurable value, and access to the data or knowledge required to build and test the solution. 

A previous Miami AI Engineering team built and deployed a SharePoint-grounded RAG knowledge platform for a global venue technology company, including role-aware governance, a prompt library, architecture documentation, and an MVP deployed inside the partner’s tenant. 
Benefits For Industry Partners
Partners  receive:
  • MVP AI assistant or automated analytical workflow
  • RAG or agentic AI architecture
  • Prompt library and guided workflows
  • Governance and guardrail framework
  • Evaluation and performance results
  • Cost and ROI analysis
  • Technical documentation and implementation guidance
  • Executive product demonstration
  • Early access to emerging Miami Business School AI talent
The Miami Digital-First Lab has already shipped AI systems spanning knowledge management, document intelligence, predictive modeling, financial analysis, career technology, and enterprise workflows. 

Project Modality Fully Remote
Industry Partner Requirements to Participate
Project Topics Artificial Intelligence & Machine Learning Data Management Innovation Product Design & Development Research, Analysis, Evaluation Software Design & Development Technology Commercialization
Target Industries Consulting & Professional Services Education & Ed-Tech Finance & Investment Health Care & Life Sciences Manufacturing & Industrial Retail & E-Commerce Software, AI & Data Transportation & Logistics
Skills & Expertise Agentic AI AI Agents AI Architecture AI Governance AI Product Development API Integration Automated Analytical Workflows Cost Optimization Data Engineering Evaluation-Driven Development Full-Stack Development Generative AI Guardrails Large Language Models LLM Evaluation LoRA Fine-Tuning Model Evaluation PII Filtering Prompt Engineering Python Retrieval-Augmented Generation (RAG) Risk Mitigation Software Engineering System Integration Technical Documentation Workflow Automation
Location Information & Preferences

Located Anywhere

Priority will be given to organizations with a meaningful AI use case, appropriate data or knowledge resources, engaged technical leadership, and potential career opportunities for exceptional students.

Sponsorship

No Sponsorship Required

Compensation

No Compensation Required

Other Requirements
Ideal partners should:
  • Bring a specific business problem where AI could create measurable value.
  • Provide appropriate access to relevant data, documents, APIs, workflows, or systems.
  • Identify the users and decision-makers the solution should support.
  • Designate an engaged technical or business leader as the primary contact.
  • Participate in regular check-ins and provide timely feedback.
  • Clarify privacy, security, governance, and deployment constraints early.
  • Attend the final demonstration.
  • Ideally have internship and/or full-time hiring pathways and be open to considering exceptional student contributors.
Projects should be substantial enough to require AI engineering, not simply routine use of ChatGPT or another off-the-shelf AI tool.
Expected Time Commitment For Project Managers 1 Hour per week
Key Program Dates Due Date
Request for Proposal published

Collaboration request published. Industry Partners may express interest in participating.

Oct 09 2026, 06:29 AM UTC
Interview

Educators will begin interviewing interested Industry Partners to discuss project ideas.

Oct 24 2026, 06:29 AM UTC
Proposal Application Deadline

Final date for Industry Partners to express interest in participating.

Jan 26 2027, 06:29 AM UTC
Finalize Project Charter

Educators and Industry Partners finalize project charters, legal documents, and background materials.

Feb 11 2027, 06:29 AM UTC
Official Program Launch

We’ll find a time on this day for you to meet with the students to kick off your project.

Mar 15 2027
Official Program End

We’ll find a time on this day for you to meet with the students to wrap up your project.

Apr 26 2027

Program Timeline

Due Date
Activities
Deliverables
Status
Action
Mon, 03/15/27
Program Kickoff
No Deliverables
No deliverables are required for this action item.
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