InverSight

Physics-inspired forecasting for finance.

InverSight helps investment and finance teams transform historical financial metrics into probability ranges, downside-risk indicators, and valuation-sensitive scenarios.

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The problem

Financial teams still rely heavily on spreadsheets and fixed scenarios. These workflows are useful, but they often hide uncertainty and depend on assumptions made in advance, which can bias outputs and make valuation risk harder to assess.

The solution

InverSight is a probabilistic forecasting platform for financial metrics. It learns from historical data and generates least-biased probability ranges of future outcomes, helping teams move from static spreadsheet scenarios to clearer, risk-aware forecasts.

What it delivers

  • Forecast probability ranges
  • Fan charts and percentiles
  • Downside-risk indicators
  • Terminal distributions
  • Valuation-sensitive scenarios

Built for

  • Investment funds
  • Family offices
  • Valuation advisors
  • Finance teams
  • Private-market investors

Founder

InverSight is founded by César Arias, a quantitative founder with a PhD in Theoretical Physics, postdoctoral experience at UC Davis and PUC Chile, a Master in Finance, and previous experience as a quantitative analyst in private investment funds.