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Case Studies

Proven results – real impact across industries. From smarter demand forecasting in Retail & E-Commerce to advanced fraud detection in Finance and AI-assisted diagnostics in Healthcare, our solutions turn complex data into measurable business value.

Fashion retailer

Retail & E-Commerce

Predictive Automation

A leading American e-commerce brand struggled with inaccurate demand forecasts that caused overstock and frequent sell-outs. We implemented an AI-driven forecasting model that analyzed sales, marketing, and seasonal data to predict demand more precisely. Fully integrated into their ERP system, it automated weekly reorder recommendations, reduced manual work, and helped teams shift from reactive decisions to a data-driven, scalable approach across operations and strategy.

    • +42 % forecast accuracy

    • −28 % excess inventory

    • 2× faster decisions

  • Overstock and manual forecasting caused cost spikes.

  • AI-driven demand forecasting integrated into ERP.

Stock Exchange

Finance

Smarter Fraud Detection

A mid-sized European fintech company faced increasing transaction delays and customer frustration due to false fraud alerts. We developed a machine-learning model that analyzed historical patterns and behavioral data to distinguish legitimate activities from real risks. Integrated seamlessly into their payment infrastructure, the AI system automated detection, accelerated approvals, and enabled a shift from reactive monitoring to proactive, intelligence-led fraud prevention.

    • −63 % false positives

    • +54 % faster approvals

    • Increased trust and retention

  • Too many false positives slowed payments.

  • Machine-learning model for real-time transaction scoring.

Doctor analyzing brain scans
Healthcare

AI Diagnostics

A regional healthcare network struggled with time-intensive manual reporting that slowed diagnostics and burdened medical staff. We introduced an AI-powered assistant capable of analyzing imaging data and pre-drafting diagnostic summaries for physician review. Integrated into their existing systems, the solution streamlined documentation, improved accuracy, and allowed doctors to dedicate more time to patient care while maintaining full compliance and data security.

    • −37 % reporting time

    • +23 % diagnostic consistency

    • Improved patient throughput

  • Manual reporting overloaded clinical teams.

  • NLP assistant pre-analyzed reports for doctors.

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