Leveraging Generative AI for Internal Excellence A 24-hour-Hackathon Experience

DATA, ANALYTICS, AND AI

OUR EXPERTISE

In 2025, AI trends emphasise data-driven decision-making, multimodal AI, and the democratisation of AI. Generative AI, AutoML, and real-time analytics enhance data insights, while multimodal AI improves decision-making and personalisation. Low-code platforms and pre-trained models make AI more accessible. Responsible AI practices focus on bias

reduction, explainable AI, and ethical guidelines. Advances in MLOps, federated learning, and AR/VR ensure quality and immersive experiences, addressing global challenges. At Accesa, we leverage these trends to deliver innovative, responsible AI solutions that transform businesses across finance, manufacturing, and retail.

Highlights

Increasing efficiency on the production line with Big Data & Analytics

Increasing efficiency on the production line with Big Data & Analytics

Manufacturing and Multi-Industry Application ModernisationData, Analytics & AI Solutions

How Accesa increased efficiency on the production line for a top woodworking company by leveraging Big Data & Analytics to identify areas of improvement.

Leveraging Generative AI for Internal Excellence: A 24-hour Hackathon Experience

Leveraging Generative AI for Internal Excellence: A 24-hour Hackathon Experience

Engineering
26th April, 2024

Discover more about our colleagues' experience participating in ShipIT, a 24-hour hackathon at Accesa, which offered an opportunity to leverage generative AI for internal solutions.

Philipp Farnschlader (AI Engineer) and Cristian Chiriac (Frontend Software Engineer) have crafted this article, which was previously featured in the April 2024 issue of Today Software Magazine.

Unlocking the Power of Data: The Benefits and Challenges of Data Lakes

Unlocking the Power of Data: The Benefits and Challenges of Data Lakes

Business
12th July, 2024

Explore how data lakes work, their advantages over other storage solutions, and the challenges organisations may face when implementing them.