Ved Patel

2x founder. Engineer. Researcher.

ABOUT

I was brought up in the Bay Area, where I first learned how to play cricket. For 6 years, I represented my academy and region in national and international tournaments before I decided to take it a step further and play professionally in India. For the next 7 years, I went from captaining my district to captaining and representing my state at a national level.

Some snippets from over the years:

I came back to the Bay Area to pursue higher education, started community college, and got my associate's degree in computer science, and transferred to UC Irvine, where I'm currently a senior. I focus on the intersection of artificial intelligence and systems engineering.

Currently, I'm co-founding and building Orderly, the multimodal AI ordering layer for every restaurant on Earth.

WORK

Orderly (2026)
Cofounder / CTO

The multimodal AI ordering layer for restaurants. Guests scan a QR code, place their order, and it is routed directly to the kitchen through the existing POS. Signed a marketplace and co-sell agreement with Shift4 in under 30 days. Paid pilot with Flynn Group, the largest restaurant franchisee in the US, launching across Applebee's.

Cisco (2026)
Software Engineer Intern

SD-WAN Team

Rezolve AI (2025-26)
Software Engineer

Architected and built the initial version of the no-code AI Agent Builder for Enterprise Automation.

Adept AI (acquired) (2025)
Cofounder

Built and sold an AI workflow automation tool for construction with my childhood best friend and current Orderly co-founder, Math Heramia. Six-figure exit in under six months.

Sandia National Laboratories (2025)
Machine Learning Research Intern

Predicting the specific DNA attachment site an integrase targets from its protein sequence is a challenge because of the missing co evolutionary signals in current representations. I built an ML pipeline using ESM-2 and DNABERT to analyze 491K+ integrase–att site pairs and biological structure with UMAP and HDBSCAN, and evaluate predictive models.

SJSU (2023-24)
Applied AI Research Intern

Did some cool research here as part of a small team on algorithmically matching dogs by personality. Collaborated with cross-functional teams for data analysis and architected solutions for recommendation systems.

RECENT PROJECTS

(2026) Provr
Built a mastery-based learning platform for any topic, skill, or career path. The idea is to reduce the amount of technical debt people accumulate while trying to rapidly learn with AI. Provr takes a unique approach by designing the curriculum from real internet videos and articles, and smartly blending AI assessments and real-world scenarios to make sure learners are acually able to prove their mastery of the content.
(2026) MCP Network Diagnostics
Made an AI powered network diagnostics platform with operator & consumer modes; features an mcp integrated monitoring agent as well as a real-time dashboard for enterprise and edge network troubleshooting.
(2026) Trajectory Instability in LLM-Based Agents
Built a framework and the trajectory divergence rate metric to quantify behavioral consistency in multi step agents.
(2026) Cross-Architecture Study of Behavioral Stability under 4-bit Quantization
Did behavioral analysis of 4-bit quantization on instruction-tuned llms; introduced a robustness coefficient & boundary distance metric to characterize behavioral stability across architectures.

education

(2025-27) University of California, Irvine
B.S. in Computer Science (Regents Scholar)
(2023-25) Las Positas College
A.S. in Computer Science

check out this neural network implementation that solves xor classification, which was a problem that proved single layer models weren't sufficient.

  • toggle inputs directly by clicking on the digits
  • press train to watch the numbers update live
  • press 'test all' to see results
  • press 'reset' to erase everything
Inputs: XOR
Epoch: 0 MSE Loss: 0.000000