Swarmalytics Moves Quantum Computing Into the Core of Its Predictive Platform, Files Provisional Patent

Asheville, NC, July 29, 2026 --(PR.com)-- Swarmalytics today announced that quantum computing now operates inside the core of its predictive modeling platform, extending from data preparation into the company's swarm intelligence engine itself. The company has filed a provisional patent covering its quantum-enabled predictive modeling methods (Provisional Application No. 64/113,065).

The first quantum capability, quantum decorrelation, works in the platform's feature engineering layer. It uses quantum computing to generate a covariance matrix across all input variables, identifying how each variable relates to every other simultaneously and producing new composite predictive components ranked by the variance they explain. Those components pass into Swarmalytics's proprietary SwarmAI platform as additional input features, giving the model signals that conventional feature engineering does not reach.

Swarmalytics has now taken quantum computing a step further, moving it out of data preparation and into the model itself. Inside the SwarmAI engine, populations of predictive agents compete and improve across generations through a process the company calls murmuration. Swarmalytics has introduced a quantum murmuration option that uses a quantum algorithm to decide which traits carry into the next generation of agents, placing quantum computation at the center of how the models learn rather than only in the steps that precede them. The quantum capability has been validated in simulation environments.

"Interactions between variables are where the real signal lives in complex datasets," said Doug Newell, CEO of Swarmalytics. "Conventional methods find some of them. Quantum computing finds the ones conventional methods miss. We have built that into the platform, we have filed a patent on it, and it is running now."

Swarmalytics has run its quantum decorrelation on quantum hardware from IonQ, a company building some of the most advanced quantum computers available today. As qubit capacity grows across the industry, the number of variable interactions the system can process in a single run will grow with it.

The quantum transformation is preserved inside the trained model, so quantum-generated features remain available for scoring and deployment without requiring quantum computation at inference time.

"We were working with AI and predictive modeling long before most people had heard the terms," Newell said. "Quantum is the same story. The organizations that understand it early and build for it now will be in a different position when the rest of the market catches up."

Swarmalytics is exploring pilot engagements with organizations that manage large, complex datasets across insurance, financial services, real estate, supermarkets, and logistics.

About Swarmalytics
Swarmalytics builds predictive analytics systems for institutional decision-makers. Founded by Doug Newell, former VP of Analytics at American Express and co-founder of seven companies, the firm has served Fortune 500 clients across financial services, insurance, and consumer markets for more than 30 years. Its proprietary SwarmAI platform uses swarm intelligence architecture to identify signal across 16,000-plus variables per data point, at machine scale.