Acubic provides a quantitative portfolio intelligence platform that uses AI to instantly filter over 70,000 assets based on user‑defined goals, then ranks and selects the best securities with a quant model. The system offers full‑strategy backtesting—including rebalancing and transaction‑cost modeling—and an institutional‑grade engine that generates optimized allocations which can be sent to a broker via a secure API for automated execution.
Funding
Funding not disclosed
Founders
Product
Problem
Self-directed investors and analysts often rely on manual spreadsheet processes or opaque tools to build and manage portfolios, leading to time‑consuming workflows, limited asset coverage, and unclear risk assumptions.
Solution
Acubic offers a quantitative portfolio intelligence platform that uses AI to filter over 70,000 assets based on user‑defined goals. Users select from transparent quant models that rank assets, after which the system generates optimized allocations and provides realistic backtesting that includes transaction costs and rebalancing logic. The platform connects to regulated brokers via a secure API, enabling one‑click order execution and automated portfolio rebalancing. All analytics are built on an institutional‑grade engine but presented through a simplified web interface, allowing medium‑risk investors to apply hedge‑fund‑level methodology without deep technical expertise.
Target Audience
Primary customers are self‑directed investors, financial analysts, and research‑oriented users who need a repeatable, transparent portfolio building workflow beyond basic spreadsheets.
Features
- AI‑driven asset universe selection answering seven goal‑setting questions, instantly narrowing 70,000+ securities
- Choose from multiple transparent quant models that score and rank assets according to defined risk tolerance
- Optimized portfolio construction with walk‑forward backtesting that incorporates real‑world transaction costs and dynamic rebalancing
- One‑click broker integration via secure APIs with major regulated brokers (Alpaca, Interactive Brokers, Charles Schwab, etc.)
- Automated execution and scheduled rebalancing to maintain target weights without manual intervention
- Public methodology documentation with versioned review dates for model assumptions and risk framing