OnePlanck develops rigorous AI-powered research and decision-support systems for financial markets — combining machine learning, quantitative methods, market data, and agentic AI.
OnePlanck is developing systems that help researchers and financial professionals move from data and evidence to reproducible experiments, robust evaluation, and decision support.
AI-assisted workflows for research planning, evidence synthesis, coding, experiment analysis, and technical reporting. The system is designed to integrate frontier language models, including Claude, as reasoning and agentic components.
In developmentStructured analysis of market data, financial information, and research evidence for quantitative investigation and hypothesis generation.
Research prototypeTools for stress-testing financial ML systems across market regimes, transaction costs, assumptions, distribution shifts, and decision-relevant conditions.
Research-ledResearch interfaces that connect model outputs, uncertainty, evidence, and human judgment without promising investment returns.
ExploratoryOur agentic research workflows are designed around rigorous evidence handling, reproducible experimentation, and safe human oversight. Claude is a natural fit for reasoning-heavy tasks such as research planning, synthesis, coding assistance, experiment interpretation, and technical reporting.
Our research program spans machine learning for financial forecasting, reinforcement learning, robust evaluation, agentic AI, and quantitative decision systems.
We study how predictive systems behave when market conditions, data-generating processes, and economic constraints shift over time.
We investigate learning and evaluation methods for sequential decision-making where transaction costs, risk, and regime dependence matter.
Our work emphasizes reproducibility, claim auditing, stress testing, and decision-relevant evaluation rather than single benchmark numbers.
We explore how frontier language models can support research planning, evidence synthesis, coding, experiment analysis, and technical reporting while keeping human researchers in control.
OnePlanck is an AI research and technology company focused on quantitative finance. We combine machine learning, quantitative methods, financial data, and agentic AI to develop rigorous research and decision-support systems.
Our approach is grounded in peer-reviewed research and a simple principle: financial AI should be evaluated under the conditions in which real decisions are made.
OnePlanck's technical direction is informed by an active body of peer-reviewed work in machine learning and quantitative finance. The research foundation spans four areas that directly shape the systems we are building.
Predictive modeling, market regimes, distribution shifts, and robust empirical evaluation.
Sequential decision-making for financial research and trading systems under realistic constraints.
Stress testing, claim validation, reproducibility, and evidence-driven system assessment.
AI-assisted research planning, synthesis, coding, experiment analysis, and scientific reporting.
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