Mays Business School Names 12 Finalists for AI Venture Velocity Challenge, $100K on the Line
National competition rewards student founders for how quickly and effectively they think, test, build, and validate with AI, not how well they polish a pitch. Finals are Sept. 26 at Texas A&M’s Mays Business School.
Texas A&M University’s Mays Business School has named 12 finalists in its AI Venture Velocity Challenge, narrowed from the 531 teams that entered the competition’s inaugural year and the 27 semifinalists announced in July. The finalists will compete Sept. 26 at Mays Business School for $175,000 in non-dilutive funding, including a $100,000 top prize, in a live final open to the public.
The challenge, organized by Mays’ Center for Applied Entrepreneurship and Innovation, was built to reward a different kind of founder. Rather than scoring teams on stage presence or product demos, judges evaluate finalists against a published rubric weighing problem significance, learning velocity and experimentation rigor, how effectively teams leveraged AI, evidence of real venture progress, responsible and ethical design, and how well founders adapted when the evidence told them to. It is a method built on a simple premise: the habits that lead to good decisions matter more than the decisions themselves.
That method came into focus during Stage 2. The strongest teams identified assumptions that could determine whether their ventures should exist, designed meaningful tests, and used AI to move faster from critical questions to credible evidence. They combined AI-enabled research and building with customer discovery, technical validation and direct market interaction. When evidence challenged their assumptions, they adapted. That combination of learning velocity, sound judgment and meaningful venture progress separated the finalists.
“What impressed us most was not simply what these teams built, but how they learned,” said Levi Belnap, executive director of the Center for Applied Entrepreneurship and Innovation at Mays Business School. “They used AI to move faster without outsourcing judgment to it. They tested assumptions that could make or break their ventures, listened carefully to customers and other evidence, and changed course when needed. That discipline is exactly what we designed this challenge to reward.”
The finalist ventures span industries from agriculture to healthcare to assistive technology, including a team using AI to help prevent livestock mortality on farms and another working to match cancer patients with the right clinical trials. Several finalists already have paying customers, signed letters of intent or pilot commitments, demonstrating how disciplined experimentation can lead to tangible market validation.
At the Sept. 26 finals, each team will walk a panel of industry-leading judges, and spectators, through the assumptions they tested, the evidence they gathered, and the pivots that evidence forced. Investors, employers, educators, and community members interested in entrepreneurship and AI are invited to attend and watch the teams defend their evidence in person. To RSVP, visit mays.tamu.edu/ai/competition.
After the finals, Mays will release a full report drawing on the public dashboard of experimentation patterns, pivot rates, and AI use across all 531 teams that entered this year, one of the most detailed public datasets to date on how student founders are actually using AI to build companies, not just talk about it. It is one piece of a broader investment in AI at Mays focused on preparing students for what’s ahead, expanding AI-focused coursework, research, and industry partnerships across its undergraduate, graduate, and doctoral programs, and training students not just to use AI tools, but also to know when human judgement should take over.
As the AI Venture Velocity Challenge heads into its finals, the top 12 teams are setting the standard for what disciplined, evidence-driven entrepreneurship looks like in the AI era.
The 12 finalist ventures are:
Do Si
University | College: The University of Tulsa | McDougall School of Petroleum Engineering; Tulane University | School of Science & Engineering
Team: Vusal Karimov; Toghrul Azizli
Academic Profile: Ph.D. students in petroleum engineering and chemical and biomolecular engineering
Industry: Biotechnology and drug discovery
Venture Synopsis: Do Si is developing failure-aware AI to identify potentially toxic molecules earlier in drug development. The team advanced by challenging its own technical assumptions, improving explainability and privacy, and grounding the product more directly in pharmaceutical workflows and buyer needs.
EntroPINN
University | College: University of California, Berkeley | College of Chemistry; College of Computing, Data Science, and Society
Team: Nathan Liu; Dongha (David) Kim; Christopher Donahue
Academic Profile: Undergraduate students in chemical engineering and computer science
Industry: Industrial engineering software and energy efficiency
Venture Synopsis: EntroPINN is building a physics-informed AI copilot that helps engineers optimize industrial processes with fewer costly simulations. The team advanced through rigorous technical benchmarking, direct industry discovery, and a disciplined decision to narrow its scope when broader generalization did not hold.
Lobe AI
University | College: Texas A&M University | College of Engineering; Mays Business School
Team: Tiernan Lindauer; Shubh Bhakta
Academic profile: Undergraduate students in computer science, physics, and finance
Industry: Senior living sales technology
Venture Synopsis: Lobe AI provides an AI sales assistant that engages families visiting senior living websites, schedules tours, and prepares community sales teams for follow-up. The team advanced after translating customer discovery into a live paid contract, additional customer commitments, and a pathway to broader deployment.
MottoNote
University | College: University of Wisconsin-Madison | College of Computing and Artificial Intelligence
Team: Siddharth Singh; Viacheslav Iudenko
Academic Profile: Undergraduate students in computer science
Industry: Enterprise knowledge management
Venture Synopsis: MottoNote turns unstructured organizational information into a continuously updated knowledge graph that AI systems can use. The team advanced by measuring real customer behavior, increasing adoption, and allowing usage evidence to overturn a requested feature and reshape the product.
NEXUS
University: Baylor College of Medicine; Columbia University
Team: Shay Beheshti; Brooke Dirvin
Academic Profile: Graduate students in genetics and genomics and in genetics and development
Industry: Oncology and clinical trials
Venture Synopsis: NEXUS is developing an AI system that matches cancer patients with clinical trials based on their medical records. The team advanced after securing an institutional pilot commitment and adapting the product around clinical integration, governance, and the realities of healthcare adoption.
Oncera Health
University | College: University of Texas at Austin | College of Natural Sciences
Team: Rutu Ruparel
Academic Profile: Undergraduate student in molecular and cellular biology
Industry: Oncology survivorship and digital health
Venture Synopsis: Oncera Health is building a personalized digital platform to help cancer survivors manage recovery after treatment. The team advanced by connecting patient needs with reimbursement research, institutional pilot interest, and direct engagement with health system stakeholders.
OsageMD
University | College: Texas A&M University | Mays Business School
Team: Matthew Schaefer
Academic Profile: Graduate MBA student
Industry: Healthcare operations and legal technology
Venture Synopsis: OsageMD is building a HIPAA-compliant case-management platform for medical lien financing workflows. The team advanced by combining held-out technical testing with direct workflow research, economic-buyer interviews, and meaningful interest in paid pilots.
Parkevo
University | College: High Point University | Earl N. Phillips School of Business
Team: Evan Taylor; Brianna Stinespring
Academic Profile: Undergraduate students in finance and social media and digital communication
Industry: Smart mobility and parking technology
Venture Synopsis: Parkevo uses edge AI to provide real-time parking availability and utilization analytics. The team advanced through a signed university pilot, production-oriented technical deployment, and extensive discovery across several institutional parking markets.
Reliat
University | College: Texas A&M University | College of Engineering
Team: Alice Queiroz; Phuong (Alex) Dao
Academic Profile: Undergraduate students in electrical engineering and data engineering
Industry: Mining and industrial AI
Venture Synopsis: Reliat is developing AI-powered intelligence for critical mining and aggregate operations. The team advanced by narrowing its initial concept to a more valuable market entry point, securing an industry partnership and changing its architecture, pricing, and customer definition as evidence emerged.
Smart Swine
University | College: Texas A&M University | College of Agriculture and Life Sciences; College of Engineering
Team: Ziyuan Zhao; Yu Wang; Emmanuel Otchere; Rolando Alaniz
Academic Profile: Three Ph.D. students in poultry science and one graduate student in engineering technology
Industry: Agricultural technology and animal health
Venture Synopsis: Smart Swine uses precision livestock AI to reduce piglet mortality and improve outcomes for pork producers. The team advanced by moving years of research into a commercial-farm deployment, testing its pricing assumptions, and earning meaningful interest from operators.
SpeechRoot (formerly VoiceVault)
University | College: Texas A&M University | College of Engineering
Team: Zarik Khan
Academic Profile: Undergraduate computer science student
Industry: Assistive communication and digital health
Venture Synopsis: SpeechRoot is building an AI voice-personalization layer for people who use augmentative and alternative communication devices or face permanent voice loss. The team advanced by responding to clinical feedback, earning a pilot commitment, establishing a reproducible voice benchmark, and exploring reimbursement and distribution pathways.
ZERO1 IO
University: University of Silicon Valley
Team: Aisha Medina; Suman Dangol
Academic Profile: Graduate students in the Master of Business Innovation program
Industry: Enterprise operations and manufacturing AI
Venture Synopsis: ZERO1 IO develops private AI agents for complex operational workflows. The team advanced after embedded customer observation led it away from a less-repeatable delivery model toward a focused manufacturing workflow and paid customer validation.
About Mays Business School
Texas A&M University’s Mays Business School is building a better future through business. By providing leadership-centered, experiential education to more than 8,000 undergraduate, master’s, and doctoral students in accounting, finance, management, management information systems, marketing, and supply chain management, Mays consistently ranks among the top public business schools nationally for its programs and faculty research. Our mission is developing leaders of character who make a positive difference in the communities where they live, work, and serve.
