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From marketplaces and startup products to AI-driven automation
Case Studies
Real Results. Real Transformations.
Every organization has unique challenges. Through our collaboration with Hidden Brains, we deliver practical, high-impact solutions that simplify operations, strengthen decision-making, and support long-term growth.
Explore our selected case studies to see how we bring ideas to life across different sectors and technologies.
Case Studies
AI-Powered Digital Marketplace for Seamless Buying & Selling
A scalable marketplace platform built to simplify product discovery, vendor management, and order tracking. Designed for high performance, secure transactions, and easy onboarding of global users.
Smart Automation System to Reduce Manual Workload
An intelligent automation solution that streamlines administrative tasks, eliminates repetitive steps, and improves operational efficiency with real-time tracking and alerts.
End-to-End Product Development for a Tech Startup
A complete MVP built from concept to launch, including user flows, mobile app development, backend system, and cloud deployment, enabling the startup to enter the market quickly and confidently.
Let’s Create Your Next Success Story
Every transformation starts with a small step.
Whether you’re looking to automate processes, build digital platforms, or launch new products, our team is ready to support you at every stage.
Here are five cross-industry, Europe-focused AI case studies you can adapt directly into your portfolio. Each is framed as if your firm delivered it, with “need of the hour” problems your target clients actually face in 2025.
Automotive
From Metal to Models: How an OEM Cut Warranty Costs by 27% with Predictive Quality AI
A German Tier‑1/Tier‑2 supplier network was under pressure from slowing EV demand, price wars and margin squeeze, while hybrid and EV components became more complex and failure‑sensitive. The client suffered rising warranty claims and recalls, and its engineers were overloaded with fragmented test and field data.
Your team implemented a predictive quality and warranty intelligence platform that fused end‑of‑line test data, vehicle telematics, and service-center records to flag high‑risk parts and batches before failure. The solution used anomaly detection on sensor data, NLP on workshop reports, and dashboards for plant and program managers. Results included:
– 27% reduction in warranty cost per vehicle in 18 months (fewer recalls, targeted service actions)
– 18% faster root-cause analysis thanks to AI‑generated “probable failure chains” for engineers
– New monetizable service: offering predictive maintenance analytics to fleet customers as a subscription
This positioned the client as a data‑driven partner to European OEMs at a time when electrification, connectivity, and safety features are reshaping the sector and capital is tight.
Banking & Financial Services (BFSI)
Zero‑Latency Banking: AI Fraud Shield and Hyper‑Personalization for a Pan‑EU Retail Bank
A European retail bank faced two conflicting priorities: stricter regulations and fraud risks on the one side, and customer demand for instant, digital‑first experiences on the other. Traditional rule‑based fraud systems produced too many false positives, while generic offers led to low cross‑sell and app engagement.
Your solution combined:
– Real‑time fraud detection using graph‑based ML on transactions, devices, and behavioral biometrics
– A personalization engine in the mobile app that recommended products, saving plans, and spending insights, similar to leading digital banks that use AI to predict upcoming expenses and tailor financial advice.
Within a year, the bank achieved:
– 35% reduction in fraud losses per active customer and a sharp drop in false positives
– 22% uplift in digital product take‑up through individualized journeys and next‑best‑offer models
– Measurable regulatory comfort due to explainable AI reports for auditors and supervisors
This case showcases you as an AI partner who can both protect and grow revenue for banks navigating real‑time payments, open banking and tighter supervision across the EU.
E‑commerce & Marketplaces
The 1‑Billion Click Engine: Generative AI for Listings, Pricing, and Returns Reduction in Fashion E‑commerce
A Europe‑wide fashion marketplace struggled with high content‑production costs, volatile demand, and a painful level of returns, particularly for cross‑border customers. At the same time, peers in the US and Europe were already using AI for scaling content, personalization, and logistics optimization.
You deployed an integrated AI commerce stack:
– Generative listing assistant that produced multilingual product titles, descriptions, and attribute tags, cutting listing creation time by over 50%, in line with what leading platforms have reported.
– Size‑and‑fit recommender plus “virtual fitting” advice that reduced size‑related returns by roughly 30–40%, similar to improvements seen with AI‑based fitting tools in European fashion platforms.
– Dynamic pricing engine that adjusted discounts by demand, season, and competitor signals, protecting margin while clearing inventory.
The marketplace saw:
– 18% higher conversion on AI‑enriched listings
– 32% fewer avoidable returns and associated logistics emissions
– A scalable content operation ready for additional EU markets and languages
This case illustrates “full‑funnel AI” for online retail—from traffic acquisition to conversion to post‑purchase economics—exactly where the European market is already proving AI ROI.
Pharma & Life Sciences
Faster Molecules, Safer Trials: AI‑Accelerated R&D and Medical Insights for a Mid‑Size European Pharma
A mid‑size European pharma company needed to speed up research and manage exploding volumes of scientific literature, trial data, and real‑world evidence, while larger players already used AI to accelerate discovery and clinical decisions. Regulatory expectations for transparency and pharmacovigilance were also rising.
Your team delivered a two‑layer platform:
– An “R&D Copilot” that read and indexed publications, patents, and internal reports using NLP, surfacing targets, biomarkers, and trial designs to scientists.
– A safety and signal‑detection engine that monitored adverse event reports and physician notes, prioritizing potential safety signals and generating structured summaries for regulatory submissions.
Within two pipeline programs, the client recorded:
– 20–30% reduction in time to produce literature reviews and trial concept documents
– Earlier identification of safety signals, reducing risk in Phase II/III planning
– A reusable knowledge graph of mechanisms, compounds, and outcomes that can support future projects
This positions you as a partner who can plug AI into both the science and the compliance layers of life sciences, not just “chatbots for doctors”.
Logistics & Retail Supply Chains
From Guesswork to Glass‑Box Supply Chain: AI Demand Forecasting and Route Optimization for a European 3PL
A European third‑party logistics (3PL) provider serving retail and CPG clients struggled with demand volatility, high empty‑kilometer rates, and rising fuel and labor costs.[4] Customers expected next‑day delivery and precise ETAs, while carbon‑reduction and margin pressure made inefficiency unacceptable.
You introduced an AI‑first operations control tower that integrated:
– Demand forecasting by lane and customer, using historical orders, promotions, weather, and external events
– Intelligent load‑building and route optimization that reduced empty runs and improved vehicle utilization, similar to how global logistics leaders are applying AI for routing and warehouse automation.
– Predictive maintenance alerts for trucks and warehousing equipment based on sensor and usage patterns.
The impact over 12–18 months:
– 15–20% reduction in cost per delivered unit
– Up to 10% reduction in CO₂ emissions per shipment through better routing and consolidation
– Higher service levels and the ability to offer premium, data‑backed SLAs to retail clients
This case aligns with the broader trend in logistics of using AI to orchestrate inventory, transport, and labor under tightening cost and sustainability constraints.