Probabilistic forecasts
Review time bound stock forecasts as ranges, with a base case and uncertainty made visible alongside the estimate.
Explore forecastsAI powered product company
Vaniras builds AI powered applications that turn complex evidence into clearer decisions. Our first product is a machine learning platform for market intelligence and probabilistic stock forecasting.
First product
Markets do not offer certainty. Vaniras brings forecasts, ranges, context, and model evidence into one place so investors and research teams can examine what may happen next without mistaking an estimate for an outcome.
The platform supports research. It does not execute trades, provide personalized financial advice, or guarantee investment results.
Review time bound stock forecasts as ranges, with a base case and uncertainty made visible alongside the estimate.
Explore forecastsScan market coverage visually, then move from the field view into the evidence behind an individual company.
Open the heatmapKeep the companies you follow in one research surface and return as prices, forecasts, and context change.
Build a watchlistBring forecasts together with charts, company information, market context, and supporting analysis.
View market intelligenceInside the product

Forecast workflow
Prepare market and company data for the model pipeline.
Generate horizon specific machine learning forecasts for the supported universe.
Present a base case with upper and lower bounds instead of a guaranteed price.
Track forecasts against later outcomes and keep methodology, dates, and model context close to the output.
Built for considered decisions
A clearer way to compare model estimates, uncertainty, and company context before doing deeper research.
A shared surface for scanning coverage, following names, and examining evidence across a consistent workflow.
A foundation for conversations about responsible AI products, market research workflows, and applied machine learning.
Trust is part of the product
We separate numeric forecasts from explanatory content, preserve dates and model context, and state the limits of decision support plainly. The product is designed to help people inspect evidence, not outsource judgment.
Forecast dates, ranges, horizons, and methodology belong near the output.
Machine learning generates numeric estimates; the interface delivers them with supporting research context.
Authentication protects account features, while sensitive service credentials remain server side.
No guaranteed returns, automated trading, or personalized financial advice.
Market intelligence is Vaniras's first product domain, not its final boundary. We are building the product, evaluation, and trust disciplines needed to create AI powered applications in other evidence heavy fields.
About VanirasSelected insights
Forecasting
Why a useful market forecast should communicate a range of outcomes, its horizon, and the uncertainty around the estimate.
Read noteMarket Intelligence
A practical guide to base cases, upper and lower bounds, model confidence, and why those elements should be read together.
Read noteResponsible AI
What transparency can look like in a forecasting product, from model versioning and dates to ranges and evaluation records.
Read noteThe product is live
Open the Vaniras application for forecasts, the heatmap, watchlists, stock intelligence, charts, and market analysis.
Open the application