About Acubic
Last updated: April 2026
What we build
Acubic is a quantitative portfolio intelligence platform built around portfolio optimization, AI-assisted portfolio building, risk profiling, and walk-forward backtesting.
The product is built around portfolio intelligence — not one-click speculation. Every workflow prioritizes transparent constraints, interpretable assumptions, and repeatable methodology over black-box outputs.
Who Acubic is for
Acubic is designed for self-directed investors, financial analysts, and research-driven users who want a more structured, repeatable portfolio process. The platform is especially relevant when spreadsheet workflows start to feel too manual and existing tools feel too opaque about their underlying logic.
Research and methodology standards
Acubic publishes public methodology pages and guides that explain how portfolio construction, risk framing, and validation should work in practice. These pages are reviewed when major product workflows, model assumptions, or data handling choices materially change. Significant updates are reflected with visible review dates on affected pages.
Research content is written to be citable and honest about limitations. Where claims about model behavior are made, they are based on documented backtesting or explicit analytical assumptions — not marketing generalities.
Trust signals
Public trust signals currently available on the platform include:
- Transparent pricing with no hidden fees
- Methodology documentation with review dates
- Practical research guides on portfolio optimization, risk profiling, and backtesting
- Privacy and Terms pages governing data handling and platform use
- Visible contact channels for support and privacy questions
What users should understand
Acubic provides research workflows and analytical tooling, not individualized financial advice. The platform is not a registered investment advisor, broker-dealer, or fiduciary. Users are responsible for evaluating suitability, execution quality, and jurisdiction-specific obligations before making live investment decisions.
Backtested and modeled results have inherent limitations. Historical performance does not guarantee future outcomes. Model assumptions may degrade during structural market regime changes, and execution quality in live markets can differ from simulated assumptions.
Contact
For support and general questions: [email protected]
For privacy and data questions: [email protected]