Turn AI into measurable value for your organisation

Exa is an AI company that develops a search engine and API that enable AI systems to intelligently search and analyse the internet. Their technology is used across domains such as finance, coding agents, news, recruitment and consulting, where large volumes of online data are quickly retrieved, structured and summarised for specific use cases.

Dedimo wanted to explore how AI could help automatically transcribe therapy sessions between client and therapist and generate reports.

When the regular Analytics Translator of a service organisation went on maternity leave, the team sought our help to ensure ongoing AI projects ran smoothly. At the same time, the organisation wanted a fresh, external perspective: how was the role being filled, and where could improvements be made?

Since the launch of ChatGPT, an increasing number of organisations have been exploring the question: "How can we apply AI within our organisation?" At this hotel chain as well, employees have already been using AI applications on their own initiative and recognise the potential to scale their use further. They sought pragmatic AI applications tailored to their domain and an approach focused on creating business value. The hotel chain engaged with multiple partners and ultimately chose to work with us. Our pragmatic approach was the decisive factor in their decision.

Financial institutions need to process large amounts of documentation. For this particular institution, an internal team facilitates this by, for example, creating summaries using text analysis and natural language processing (NLP). They make these available to the various business units. To conduct audits more efficiently, they wanted to develop a question-and-answer model to get the right information to them faster. When ChatGPT was launched, they asked us to create a proof of concept.

AI that creates a holiday itinerary or drafts an email in seconds already feels completely normal. That speed creates expectations. You may recognise this within your own organisation: if AI can do this at home, why shouldn't it be able to support business processes just as easily?

There is a clear difference between teams that occasionally achieve decent results with Claude Code and teams that consistently produce high-quality output. That difference rarely comes down to better prompts. In practice, it is usually something more fundamental: the rules and expectations you establish before the agent starts writing.

For professionals in data, analytics, martech and customer experience, Digital Velocity is one of the events where developments become tangible. It brings together practitioners, partners and industry leaders to show how they approach AI, real-time data and customer experience in practice.

Large Language Models (LLMs) have quickly become a standard component in modern applications. Most developers start by integrating models such as OpenAI, Claude or similar providers through APIs. It is fast, convenient and requires very little infrastructure.

Artificial Intelligence is transforming how you design, build, and maintain digital solutions. From code generation to data pipeline automation, AI has become a trusted companion in technical workflows.

Analysing hundreds or thousands of open answers from surveys, interviews or reviews is time-consuming. To better understand those answers, we group them into themes (for example: ease of use, service, delivery or reliability). At Digital Power, we use Large Language Models (LLMs) to quickly categorise high volumes of open answers. Our team built our own secure, transparent tool that lets us see exactly what happens under the hood. But is AI already advanced enough to replace our human researchers?

Artificial Intelligence (AI) is changing the way organisations operate, from personalised customer experiences to automated or assisted decision making, AI helps your organisation leverage your data. However, navigating through this fast-evolving field can feel overwhelming, with terms like AI, Generative AI (GenAI) & Machine Learning (ML) often causing confusion.

With the ongoing developments in the data and AI industry, the hype around AI agents has no signs of slowing down. Jensen Huang, Nvidia CEO, is a strong proponent of AI agents, envisioning a multi-trillion-dollar opportunity, where agents can perform tasks with a high degree of autonomy and revolutionize how people work and how businesses operate. So, in this article we would like to discuss what exactly AI agents are, what are their main components, how they interact together and the basics on how to build one.

Many organisations are feeling the pressure: AI suddenly seems to be high on the agenda everywhere. New tools are following each other at lightning speed, colleagues are experimenting with ChatGPT, customers are asking smarter questions, and in the media, the word “AI” is unmissable. It feels like a train has taken off, and no one wants to be left behind.

With the increasing availability of cloud services that enable companies to leverage Large Language Models, it becomes relatively easy to setup your own GPT-model. However, one important question needs to be answered before you start building: what are the benefits for my organisation?

The AI Document Explorer (AIDE) is a cloud solution developed by Digital Power that utilises OpenAI's GPT model. It can be deployed to quickly gain insights into company documents. AIDE securely indexes your files, enabling you to ask questions about your own documents. Not only does it provide you with the answers you are looking for, but it also references the locations where these answers are found.