SSi is built around a simple thesis: structured data explains what already happened, while narratives shape what the price does next. Instead of treating every post, article and search spike as equally meaningful, the platform filters noise with buzz thresholds and statistical scoring, then tries to explain the reasoning behind a sentiment shift. The result is meant to be read by an analyst, not just a machine — each signal carries a stated confidence level so a research or risk team can decide how much weight to give it.
The product covers four workflows. Equity research teams can screen by narrative momentum rather than price alone. Active traders and advisors get pre-market signals and alerts on medium-term momentum. Risk officers and portfolio managers use it to spot narrative-driven risk early. ESG and impact funds track sentiment shifts before rating agencies publish. The vendor describes the system as continuously improving: live trades and trade logs are fed back into threshold and model tuning so alerts get faster and risk controls get tighter.
The site advertises a 30-day free trial and a contact-for-pricing commercial model, so terms are set through a sales conversation rather than a public price list. FinSoftAI publishes its own live-trading statistics, including an annualized return, a win rate and a profit factor over a stated window; these are vendor-reported figures from a limited sample and should be treated as illustrative, not predictive.
