HyperC is building the research platform for robots that make money — an applied AI research and productization company in Silicon Valley, founded in 2019. We build the models and infrastructure, operate experiments, publish evidence, and bring together people interested in what happens when AI moves from advising businesses to operating them. We dream of truly useful AI systems that will eliminate poverty, save the Earth and propel humanity to the stars — and we measure ourselves in customer-realized profit, not demos.
CriticalHop starts in classical AI planning — Fast Downward distributions, the ordered library (entropy-controlled contexts in Python), metaplanner research. The lesson: automation fails at the decision, not the plumbing.
Seven years of foundational work on PARML — Profit-as-Regression Machine Learning — culminating in P34: a decision model trained against realized economic outcomes, deployed live in Amazon wholesale, micro-lending and crypto routing.
The working paper formalizes computable markets and the MSD data contract; the membership opens the model to builders; enterprise deployments carry it into governed production. The category: the Self-Driving Business AI Model — the decision core of a larger project, the research platform for robots that make money.
The short version: build robots that make money — and learn how they should operate in the world. Businesses make enormous numbers of decisions about what to buy, produce, price, move, finance and hold — and much of that coordination still runs on spreadsheets, fixed rules, meetings and intuition. Our long-range thesis is that economic intelligence can become programmable: AI systems that evaluate more possibilities, enforce constraints consistently, and automate more of the operational work of moving a business toward its objectives.
The civilization-scale narrative is an abundance economy: less wasted inventory and capital, more efficient supply chains, broader access to sophisticated decision tools — and more human time spent choosing goals rather than manually operating the machinery of commerce. The near-term experiment is whether AI can operate profitable business loops; the long-term question is what happens when increasingly capable autonomous businesses reduce the cost of decisions, coordination, logistics, risk management and production across the economy.
| Legal entity | CRITICALHOP INC., d.b.a. HyperC — Delaware C-Corporation, founded 2019 |
| Headquarters | Silicon Valley, California |
| Products | P34 · PARML · HyperC |
| Founders | Andrew Gree (Director, CEO, lead developer) · Tyler Hoffman (co-founder) |
| Backing | DVC (Davidov's Collective), which lists HyperC publicly in its portfolio |
| IP position | Filed provisional patent; multiple published defensive publications |
| Category site | computablemarkets.com |
We publish working papers, a proposed data contract for the category, and a defined falsification protocol — while shipping a commercial product measured directly in customer-realized profit. Research keeps the product honest; the product keeps the research grounded.
We hire researchers and engineers who want their models graded by a P&L. Write to careers@hyperc.com.