HyperNorm AI
HyperNorm AI sells an AI decision platform to registered investment advisers, wealth managers, fund managers and fintech platforms. It ranks which client portfolios need attention and maps market events, earnings surprises and central bank moves to each client's holdings in plain language. It then suggests actions filtered through each client's risk profile and mandate, with scenario analysis.
It also turns client meetings into tasks and portfolio actions and tracks progress toward clients' goals. HyperNorm says it has enriched more than 70 million events, reaches 65 percent directional accuracy on stock and fund price predictions and lets advisers handle four times as many clients. Its privacy policy says data is stored on AWS.
HyperNorm AI was founded in 2024 and has offices in Bengaluru and Wilmington, Delaware.
Capability Axes
Capability grades
15 of 15 axes rated · 5 graded A or B
Portfolios get ranked by urgency and risk, market events get mapped to client holdings and meetings turn into tasks, and models do each step.
Alerts and mandate aligned suggestions go to the adviser, but the meeting tool turns conversations into portfolio actions automatically, with no approval step described first.
The 65 percent directional accuracy on price predictions comes with no method, period or sample, and recommendations carry no explanation a reviewer could check.
Seventy million enriched events and a claimed fourfold gain in adviser capacity are the evidence, and no client stands behind either figure.
Training on client portfolios and adviser decisions is never ruled in or out, and how one firm's data is separated from another's isn't explained.
The June 25, 2025 privacy policy reaches the platform and spells out the sensitive data it collects, from income and net worth to Indian tax and demat identifiers. Retention is set case by case, with deletion on request.
HTTPS transmission is the only security measure described, and no attestation backs it.
Suggestions feed advice that carries fiduciary and suitability duties in each market, and HyperNorm leaves its own regulatory footing unstated.
Shared models generate suggestions for many advisers at once, so a tilt toward certain assets would repeat from firm to firm. Recommendation patterns aren't monitored in any way HyperNorm reports.
Advisers keep responsibility for acting on a suggestion, and a wrong prediction carries no published commitment from HyperNorm.
Google Analytics and Mixpanel are named, but not the models or market data vendors behind the signals.
Not one custodian, portfolio system or CRM connection is named, and no API documentation is public.
AWS stores the data in an unnamed region, under a privacy policy governed by Indian law, which leaves US clients without a residency answer.
The site settles nothing about cost, whether it runs per adviser, per portfolio or by assets covered.
Registered investment advisers, fund managers and retail investor platforms are all on the buyer list, served from offices in the United States and India.
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Pricing
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