Jadion.AI builds machine learning systems that earn trust — rigorous, interpretable, and designed for the decisions that actually matter.
Most AI vendors optimize for demos. We optimize for decisions. The highest-stakes problems in finance, operations, and risk management require systems that are rigorous, interpretable, and built with institutional accountability in mind.
We come from inside the machine. We've built hedge risk models, priced $130B pipelines, and led responsible AI frameworks at scale. Jadion.AI is what we wish had existed.
Engagements are available as retained fractional partnerships or defined project scopes. The right model depends on where you are.
End-to-end architecture for high-stakes predictive systems. Feature engineering, model development, production deployment, and monitoring built to survive regulatory scrutiny and real market volatility.
Governance, interpretability, and model risk management designed to satisfy both compliance requirements and intellectual honesty. Not theater — actual rigor, built into the development lifecycle from day one.
Specialized ML for mortgage banking, hedging, servicing, and pricing. Pull-through prediction, MSR portfolio analytics, algorithmic pricing infrastructure, and recapture modeling at pipeline scale.
Architecture and roadmap for enterprise data ecosystems — from legacy modernization to cloud-native builds. Designed for analytics reliability, AI readiness, and the operational trust that makes both possible.
Fractional leadership and embedded partnership to build data science functions from the ground up, or to restructure teams that have stopped delivering. Hiring frameworks, operating models, and mentorship infrastructure included.
Ongoing fractional leadership embedded in your organization. Best for teams that need senior data science judgment present week over week: strategy, technical oversight, people leadership, and stakeholder translation all included.
Defined scope, defined outcome. Best for organizations with a specific problem to solve: a model to build, a governance framework to establish, a platform architecture to design, or a team to restructure.
Senior Director of Data Science with 13 years building capital markets ML at Rocket Companies. Founded the Responsible AI practice, led hedge risk modeling to 4x industry accuracy, and scaled a 60-person organization spanning capital markets, servicing, legal, and compliance. Two-time TDWI national award winner. University of Michigan MIDAS research partner. Keynote speaker on AI governance and responsible deployment.
Senior Director of Engineering and former VP of Data Intelligence at Rocket Companies, where she led a 160-person organization spanning data engineering, analytics, MarTech, and enterprise data platforms. Built the trusted data foundations that power AI and ML at scale across origination, servicing, and customer experience. PSYCH-K Advanced certified. MA Economics. Native Mandarin speaker.
We are selectively engaging with founding clients. If you are building something that needs to be right, not just impressive, let's talk.
No pitch decks. No demos. Just a conversation.