Bringing a new product to market has always been a gamble. Even the most experienced manufacturers can misread market demand, overproduce, or miss a critical pricing window, resulting in a high failure rate for new products, wasted resources, and unsold inventory. Traditional forecasting methods, often based on a simple three-month rolling average, struggle to anticipate the fast-changing realities of global markets.

For manufacturers, the lifecycle of a product—launch, production, sales, and eventual discontinuance—hinges on accurate predictions. Misjudging demand can mean tying up millions in excess stock or, worse, losing customers to competitors when shelves go empty. In raw material procurement, poor forecasting can lead to buying at the wrong price or holding too much inventory, eroding profitability.

Impactive AI’s upcoming platform, Quantum Deepflow, aims to tackle these challenges head-on. Slated for its public demonstration at CES 2026, the system combines advanced AI demand forecasting with quantum machine learning. The goal is to predict not just sales patterns but the entire product lifecycle while also optimizing raw material procurement.

Deepflow can forecast raw material prices like copper, aluminum, or steel, up to six months ahead, with claimed accuracy rates of an impressive 97–98%. When it comes to predicting the commercial success of a product, accuracy ranges between 70–80%. Furthermore, the platform supports inventory management, with one industrial client reporting a remarkable 35% reduction in inventory, freeing up roughly 31 billion KRW ($22M) in cash.

The system utilizes a custom-built AI model trained on more than 60,000 variables. It combines pattern recognition with proprietary algorithms, setting it apart from traditional models. While many companies still rely on historical averages, Quantum Deepflow incorporates a broader set of signals, including market trends, seasonal patterns, and macroeconomic factors.

Impactive AI claims to leverage quantum computing through cloud-based quantum resources. This approach allows for faster training times and more nuanced predictions in complex, multi-variable scenarios—a field still under intense research with few companies utilizing this technology in their day-to-day operations.

Notably, for raw material forecasts, the platform does not require customer data, making the initial onboarding easier for manufacturers. However, inventory optimization involves creating a custom model using client-specific historical data, which tailors the system to meet individual business needs effectively.

The business goal of Quantum Deepflow is clear: to provide companies with superior forecasting capabilities that can lead to enhanced profitability. If the data presented is realistic, then the improvement in accuracy is the main selling point of the platform. During a live demonstration for a German company, Quantum Deepflow reportedly predicted daily copper and aluminum prices during a five-day exhibition with around 97% accuracy. Another case involving a steel manufacturer saw the company improve inventory forecast accuracy to 75%, far surpassing its in-house methods—a clear added-value proposition for any business.

As companies today use a mix of statistical models, enterprise resource planning (ERP) tools, and machine learning systems to manage their supply chains and resource allocation, Quantum Deepflow represents a significant breakthrough. By redefining how predictions are made, it acknowledges the intricate dependencies in supply chains and the nuances of market behavior. This system promises to empower manufacturers and suppliers alike, aiding them in better positioning their products to meet the demands of an increasingly competitive landscape.

In conclusion, Impactive AI’s Quantum Deepflow holds the potential to reshape how industries approach forecasting and inventory management. With its advanced AI and quantum computing foundation, businesses can potentially minimize waste, optimize costs, and improve effective decision-making. As the platform approaches its public unveiling, industry leaders and investors alike will be watching closely to see if Deepflow delivers on its ambitious promises.