About Dynus
Technical builders for work that matters.
Dynus is a founder-led team building custom AI layers, agentic workflows, and software for organizations that need better systems—not more tools. We bring the technical depth to understand the work and the pace to make progress quickly.
Why Dynus
AI is becoming available to everyone. Useful AI is still hard to put to work.
We started Dynus because we saw the same gap again and again: teams can see the opportunity, but translating it into software that fits their people, data, and decisions is another matter entirely. Off-the-shelf tools create possibilities; they rarely understand the work well enough to change it.
We believe every business deserves systems designed around how it actually operates. Dynus helps leaders find the high-leverage workflow, shape the right AI-enabled product, and deploy it with the care required to make it part of the business—not another experiment on the side.
Built differently
Close to the problem.
We are early in our careers, not early in our standards. Our work draws on applied mathematics, electrical engineering, venture diligence, and product building—then stays grounded in the actual workflow a client needs to improve.
That combination lets Dynus move with unusual focus: understand the operation, identify the leverage, and build the intelligent layer that makes the next decision or handoff easier.
Founders
The people behind the build.
Founder
Warren Ellsworth
Warren studies Electrical Engineering and Mathematics at Brigham Young University. He founded Dynus to help organizations turn promising AI capabilities into useful operating systems—through bespoke LLM integrations, workflow software, and practical automation.
His background includes technical diligence and unit-economics work for hard-tech investments, as well as operations work on diagnostic hardware and university technology transfer. He brings an engineer’s instinct for the system beneath the process and a builder’s focus on what can actually ship.
Co-founder
Joshua Tai
Joshua is an Applied Mathematical Sciences scholar at Brigham Young University focused on optimization, autonomous systems, cryptography, and spatial computing. He works at the level where complex models become reliable technical architecture.
His work includes a first-place Utah Governor’s Office SEDI Bounty project using zero-trust identity concepts, an autonomous scheduling and filtering prototype, and a first-place BYU × Utah AI Product Summit project. At Dynus, he brings rigor to the systems that need to reason, coordinate, and stay dependable.
Co-founder
José Raúl Ramirez Ozaeta
José studies Quantitative Economics and Econometrics at Brigham Young University. He connects product choices to customer behavior, market evidence, and the commercial outcome they are meant to create.
His experience includes customer-acquisition analysis at Capital One and generative-AI market research at General Mills, where he synthesized more than 130 consumer data signals for executive audiences. At Dynus, he helps make sure every build is not only technically compelling, but pointed at the right business problem.
