SefironAI

People researching a stock, sector, or trade today have to stitch together live quotes, SEC filings, short interest data, and prediction market odds from multiple separate tools, or rely on general AI assistants that can only browse pages piecemeal and cannot cite claims per source. Building this themselves with an agentic coding tool is possible but means wiring up a dozen data feeds, normalizing the data, plumbing citations, and encoding financial domain rules, then maintaining all of it. A full market terminal solves the data problem but costs five figures per seat. The result is that thorough, sourced financial research is either slow and manual or expensive and locked behind institutional tools.

Sefiron lets a user type a financial question in plain English and an AI agent plans the research itself: it calls market data APIs for live quotes and fundamentals, searches SEC EDGAR filings, checks FINRA data like short interest and threshold lists, pulls live odds from Kalshi and Polymarket, and searches the open web when needed, running calculations in parallel. It returns a written answer with interactive charts and a citation for every figure, along with a visible step-by-step record of the tools it called and data it used. Users can also upload their own PDFs or images for the agent to read. The site frames this as an alternative to assembling your own stack with general AI assistants or coding agents, or paying for a traditional trading-desk terminal.

The project has been tested, but I need to find the precise product- market fit.

Lining up all the data, all the assumptions and all the standards implied in finance and trading is very non trivial.