Pre-engineered features for ML-driven forecasts.
OS portfolio engineering software.
Custom solutions / research.
The ForecastOS Super Six are the 6 core beliefs that drive much of our product development efforts. Our core beliefs, in no specific order, are: 1. Institutional investors are unwilling to have platform lock-in. They want to own their IP.
We closed our US$500K all equity Pre-Seed funding round in September to help investors manage and test systematic investment processes! Our financing was led by Delphia, who incubated us over the preceding six months.
Over the last few weeks, a few professional investors have become interested in our opinionated framework for constructing and backtesting portfolios: InvestOS. We've helped them get started, and in doing so, found and fixed a couple design flaws. The result is InvestOS v0.3. A de-coupled and improved framework. This work also yielded 13 friendly guides for using InvestOS, covering
DatasetsFeaturesForecastsResults
Eliminate 80% of ML/AI forecasting work with our feature engineering as a service! For data scientists, researchers, and ML-engineers. Pull feature data from anywhere in 1 line of code.
+1350 pre-engineered featuresOpen-source portfolio engineering / optimization, backtesting, risk models, and reporting software. Enterprise support available by request.
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Custom solutions and consulting. Previous projects include dataset valuation, an app for systematic investment management, and ML-driven alpha forecasts.
Book a no-pressure call to explore our solutions. If it's a fit, we'll plan and walk you through a simple setup process.