MVP Phase

Phase Overview 

During the Minimum Viable Product (MVP) Phase participants will build upon their prototypes from the previous phase and deliver MVPs. An MVP refers to a development approach where a product is built with the minimum features necessary to satisfy the early adopters or users and gather valuable feedback for further development. During this phase, significant progress must be made to the prototypes to be considered for the Challenge MVP awards and follow-on funding opportunities.

At the conclusion of the MVP Phase, ten teams will be selected to enter the Pitch Contest and deliver a demonstration of their MVP and provide other relevant information during a 7-minute presentation. The judges select the winning teams, and each team will receive a prize as defined on the prizes page.

The Nittany AI Alliance is pursuing additional funding beyond the Challenge prizes. It is our goal to extend the Challenge experience by providing ongoing funding in the form of project funding and paid internships. These additional funding sources will be evaluated under a separate set of criteria. So, while a team may not be awarded one of the MVP prizes, it could still receive funding by way of the other forms mentioned.

Important dates for the MVP Phase include:

  • Monday, April 1, 2024, by noon (ET) — Deadline to submit MVP for internal review. Teams will receive information regarding the submittal process.
  • Friday, April 5, 2024, by noon (ET) — Deadline to submit supporting documentation for your MVP review. Teams will receive information regarding the submittal process. 
  • Wednesday, April 10, 2024, by noon (ET) — All teams will be informed whether or not they have been selected for the MVP Pitch Contest. Teams will be evaluated based on the completeness of their prototype and the accompanying documentation. A total of ten teams will be selected for the MVP Pitch Contest on Thursday, April 18. 
  • Thursday, April 18, 2024, noon to 8:00 p.m. (ET) — MVP live pitches and the 2024 Nittany AI Challenge Celebration and Networking Event, including the announcement of the top 5 MVPs and the winner of the Vishwamitra AI Geography Award. The closing ceremony will also include opportunities to meet the top Challenge teams, Nittany AI Advance interns, and members of the Nittany AI Student Society. 

The pitch, lasting no longer than seven minutes, should be focused on demonstrating the MVP, detailing how AI enables the solution, and detailing the potential benefits and impact of the solution in one or more of the following areas:

  • AI for Good — Providing a societal good that has the potential to improve the lives of others,
  • Improving Penn State operations — Improve student success and/or the student experience at Penn State.

These reviewers will include:

  • subject-matter experts related to the challenges the solution addresses
  • technical experts fluent in AI/ML capabilities
  • industry representatives
  • key decision makers from Penn State

Teams should have representatives present that can answer questions from each of the reviewers.

MVP Documentation Requirements

The supporting documentation in this round should not exceed five pages in length and should focus on supporting the criteria described below. Screenshots and graphics can be referenced in the text and included in an appendix so that these are considered outside the five-page maximum.

Cover Page

A one-page section that includes:

  • title of project
  • name, campus, and college of each team member
  • name, email, and phone number of the primary point of contact

Executive Summary

A one-page section that provides (often in bullet points):

  • project title
  • problem statement
  • solution description
  • benefits and potential impact of the solution

Overview of Project Idea

Documentation can include an overview of the problem your solution addresses and how it is being addressed. Many reviewers in this phase will not have participated as reviewers in the Prototype Phase, so this may be the first time they are seeing the MVP. Please be sure to provide enough information to ensure they understand the problem and the impact/benefit your MVP provides. Try and quantify the impact of your solution to the extent that you can.


Documentation can include a technical description of the approach the team used to achieve its goal, including the ways in which the selected AI platforms are used. A recommended approach is to provide a graphical representation that shows how the MVP utilizes the technology.

Data Sources

In this section, detail the data sources leveraged within the MVP as well as the data sources necessary for the continued development and successful implementation of the solution, beyond the MVP. If available, please detail the location and availability of the data sources and/or the plan for collecting the necessary additional data.

Team Capabilities

MVP documentation should include a section describing the detailed capabilities of the team to implement the proposed solution. At a minimum, teams should include individuals with technical expertise necessary for development of the tool and content experts with knowledge of the domain being addressed.

Criteria for Review

The following criteria will be used in the selection process for the MVP Phase of the Nittany AI Challenge.  View the full rubric (PDF).

Innovation & Technical Merit (10 points) 

  • Does the prototype demonstrate a novel use of AI, or does it improve upon existing solutions in a significant way?
  • Is the underlying AI model robust, accurate, and efficient?
  • How well has the team addressed potential technical challenges and limitations of their solution?

Impact and Relevance (10 points) 

  • Does the prototype address a pressing or significant issue within its chosen area (education, environment, humanitarianism, health)?
  • How scalable is the solution, and what potential does it have to create widespread positive change?
  • Is there clear evidence or data supporting the prototype’s potential impact?

User Experience & Accessibility (10 points)

  • Is the prototype user-friendly, intuitive, and accessible to a diverse range of users, including those with disabilities?
  • How well has the team considered the cultural, socio-economic, and demographic differences of potential users?
  • Are there mechanisms in place to collect user feedback and iterate upon it?

Ethical Considerations (10 points)

  • How well does the prototype address potential ethical concerns, including data privacy, fairness, and transparency?
  • Is there a plan in place to handle unintended consequences or misuse of the technology?
  • Has the team demonstrated an understanding of the broader societal implications of their solution?

Feasibility and Implementation (10 points)

  • How realistic is the prototype’s implementation in real-world scenarios?
  • Is there a clear roadmap for moving from the prototype stage to full deployment?
  • Has the team considered the economic, infrastructural, and regulatory challenges of their solution?