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Σternal
Agentic memory for regime-aware investing in market cycles.
Markets don’t repeat, but they rhyme. Σternal builds market memory into a decision engine by mapping today’s conditions to historical regimes. It combines macro, price, and context to surface comparable environments and an API for investors and AI agents.
Excited to share Σternal with the Product Hunt community.
We built Σternal for investors, traders, and organizations that want market context embedded directly into the way decisions get made.
Σternal maps live market conditions to historical regimes using macro structure, price behavior, and curated context, so market memory can become part of research workflows, trading and investment systems, portfolio design, and AI agents.
The idea came from a simple frustration: too much market knowledge lives in scattered notes, intuition, and static archives when it should be structured, usable, and easy to integrate.
We’re just getting started, and I’d genuinely love your feedback, especially on where this could be most useful in your workflow.
Happy to answer any questions here as well.
