Why enterprise AI is hard
AI technology has tremendous potential in the vet and pet spaces, yet many executives have yet to create sustainable value for the enterprise. Building prototypes is relatively easy, but achieving the level of accuracy needed to trust AI outputs consistently is difficult. It takes more than talented software engineers to solve complex enterprise challenges with AI, and it's expensive to build and maintain true AI engineering teams in-house.
With PupPilot, you can deploy high-quality, cost-effective AI applications to production alongside some of the best minds in AI today.
Disruptive use cases
AI has the potential to transform veterinary medicine and the pet industry in significant ways.
Improved diagnostic tools
Enhance diagnostic outputs with additional context to improve accuracy and quality of care.
Automated record-keeping
Eliminate time-consuming manual work and documentation with text summaries and generative AI.
Personalized treatment plans
Develop highly tailored treatment plans for individuals even further based on a large number of data inputs.
Predictive models for outbreaks
Use sophisticated machine learning models to make accurate predictions about potential diseases outbreaks, mutations, and spread.
<Your disruptive use case here>
Work with PupPilot to scope your own AI application based on the highest-priority needs in your business.
Our approach
PupPilot cofounder, Gary Peters, has been building enterprise AI applications since 2018 alongside leading AI experts from Stanford and Carnegie Mellon. Today, Gary and the PupPilot team employ the latest best practices when it comes to deploying AI in production, always with the intent to drive value for executives.
In 2023, PupPilot was accepted into Stanford's StartX program and gained access to world-class AI thought leaders and technologies. Leaning on this network, PupPilot is able to execute on projects and initiatives that few others can. We specialize in working with companies that have struggled to leverage AI effectively thus far - whether that's incorporating GenAI into existing workflows or building novel AI applications for new use cases. We're also happy to partner with leaders who are exploring AI for the first time to help them avoid common pitfalls.
Backed by
AI Crash Course for Veterinarians
Need a quick rundown of what's happening at the intersection of AI and veterinary medicine?
Read through our four-part blog series below.
1. Why all the hype around AI in veterinary medicine?
Get a quick overview of the current state of AI technology and what's inspiring so much innovation in veterinary medicine today.
Read Part 1 of the AI Crash Course for Veterinarians here.
2. What are neural networks and transformers?
Discover how neural networks and transformers are paving the way for cutting-edge applications in the vet and pet industries.
Read Part 2 of the AI Crash Course for Veterinarians here.
3. Where is AI excelling today?
Learn where AI is making a big difference today in the vet and pet spaces.
Read Part 3 of the AI Crash Course for Veterinarians here.
4. Where does AI still need work?
Learn which AI use cases veterinarians and executives should approach with caution today.
Read Part 4 of the AI Crash Course for Veterinarians here.
Proven AI expertise
Gary Peters Gary is a 2x startup founder who has been working in the AI space since 2018. After successful acquisitions in the fintech space, Gary is now fully focused on applying his AI knowledge in veterinary medicine where there is currently a lack of true AI engineering expertise.
Where many companies are relying on software engineers with prompt engineering skill, Gary and the PupPilot team are focused on utilizing the latest best practices when it comes to training AI, including leveraging retrieval-augmented generation (RAG) to dramatically improve LLM outputs across a variety of applications.
Gary Peters, Co-Founder PupPilot