Rethinking innovation: How AI is reshaping value creation

How do you efficiently tag thousands of apparel items? We recently helped a client tackle this time-consuming challenge by helping them build an AI system that automatically analyses product images and applies accurate tags. 

Previously, they had to manually review each product photo, note colours, characters, and themes, and enter everything into spreadsheets. It was a slow, tedious process that caused delays before products could go live on their e-commerce platform. Today, the AI solution recognises popular characters, learns from previous tags, and can be trained to identify new ones with just a few examples. The system handles 95 % of tagging with human oversight to ensure accuracy – saving time and boosting efficiency.

Is your team spending too much time responding to customer enquiries? Is it difficult to locate scattered information across systems and compose accurate, high-quality replies—often in multiple languages? It’s no surprise that this complexity can lead to frustration in customer service. 

Now imagine if AI could significantly lighten the load for the entire team. 

Here’s how: When a customer enquiry arrives, an AI agent analyses the request, identifies the intent, and retrieves the relevant information from connected systems. It then generates a context-aware response in the appropriate language. The service employee simply reviews the reply for quality before sending it. 

By providing new employees with AI-generated, accurate response drafts, they can learn company procedures and become productive members of the team much more quickly. The AI training also frees up senior agents' time, allowing them to focus on more complex issues. 

One of Northern Europe's leading housing developers, Bonava, is using AI to generate accurate home descriptions in any language within seconds. 

This automation helps teams produce more content with fewer resources, all while maintaining high quality and a consistent, targeted tone of voice. With AI in place, Bonava has significantly reduced both costs and production time across markets. While some manual input is still needed, the shift to AI has dramatically cut down on manual work, enabling the company to scale more efficiently. 

“We now have a scalable solution that’s part of an ongoing journey, with new use cases continuously being explored to meet the needs of our customers,” says Andreas Moritz, Group Head of IT and Digital at Bonava. 

Are you struggling to be CSRD compliant? Do you need to pull data from multiple sources, add new data regularly, and still end up doing a lot of manual work? Not sure you can even trust your own data? 

We recently helped a client create a single source of truth for their CSR reporting. By updating their cloud ERP, using IoT data, aggregated data, and big data benchmarking, they can now monitor key metrics and act quickly on any deviations. 

To ensure CSRD compliance in their climate accounting, we also adjusted the architecture of their data platform—adding the right data, KPIs, and reports to meet the company’s ESG reporting requirements. 

DAFA Group, a global leader in foam and rubber solutions for construction and industrial applications, provides solutions that seal, absorb, and protect customers’ products. 

The challenge was to make real-time data accessible and actionable for the entire organisation, across all departments and locations worldwide. The solution was to establish a technical foundation using Microsoft Azure and Power BI. 

“Our customers have high expectations, and the new BI solution enables us to respond faster to their needs. Data-driven decisions create value for our customers and support our ESG journey and ambitions,” says Filipa Morgado Dias BI Specialist at DAFA. 

Efficiently leveraging data, DAFA can analyse trends and address issues before they arise, significantly improving customer satisfaction.

Devold of Norway is a market leader in wool clothing across Scandinavia. 
The 170-year-old manufacturer set out to improve how they access, report on, and use data from their entire supply chain. 

The solution? Migrating all historical data from an outdated data warehouse to a modern data platform. With Microsoft Fabric, Devold now gets continuously updated BI insights and decision support—especially across production and sales. 

Production planning has taken a big step forward, with detailed optimisation, monitoring, and daily reporting. Sales operations have also had a facelift: with tighter follow-up, better profitability analysis on products, and improved financial reporting, the team now gets a clear view of what’s working—and what’s not.

E-commerce platforms are often complex, consisting of several applications with shared components. An update or change in one application can unintentionally affect others—and in the worst case, disrupt customer experience or key functionality. 

Manual testing of a composable solution like this takes time. That’s why we let AI agents based on large language models (LLMs) handle it. The agents run task-specific tests, check visible site performance, and carry out testing of the front-end application. 

Testing is now faster, more thorough—and the AI agents even catch issues that manual testers miss. On top of that, the automated testing creates a positive feedback loop, offering suggestions for improvement across the solution. 

The best part? The investment paid for itself in just two months.

What happens when one of your most critical platforms is held together by one person—and that person leaves? 
That was the risk facing a major life science distributor. Their custom platform was the link between managing bookings, documentation, and daily operations.  
 
Within the three months before that person left, we helped them create a new platform using Power Apps, Automate and Pages—connecting donors, employees, and customers in one place. Strong data encryption was a must for them, working in the tightly regulated European and US markets. 
 
It seamlessly integrates with the core business system we’re also delivering—connecting bookings, inventory and billing. That means less duplication, fewer errors, and stronger data. The best part? It’s built in popular coding language – so anyone can maintain it.

How do you efficiently tag thousands of apparel items?  

Are errors in your bid proposals causing problems in sales? Tender documents are often very detailed and complex and it can be difficult to keep track.

When submitting responses, it is essential to include every required detail–both for products and services.

We developed a digital twin AI solution that compares each bid requirement with the responses and documentation in your proposal. The result? A clear report that shows, for every product, service or feature, whether there are any deviations—along with explanations—so you can make corrections before submission.

This solution doesn’t just save time by letting your team focus on the big picture instead of the small details—it also reduces errors and improves the overall quality and accuracy of your tenders. In short: fewer mistakes, better proposals, and a stronger chance of winning the deal.