We have been implementing AI solutions since before the technology became mainstream. We know that solutions only create value when they align with data, systems and the way people work. That is why we take responsibility for the entire implementation process - from development and integration to stable production deployment. Our focus is not experimentation. It is reliable execution.
Strong solutions begin with clarity. We start by understanding business objectives, operational challenges and decision-making processes. Only then do we design the appropriate data and AI solution. Our advisory connects strategy, data and technology, ensuring that AI becomes a practical working tool that creates real value in daily operations.
by the numbers
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Years hands-on experience
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AI & Data implementations
Hidden
agendas
Our solutions are built on data and solid technical expertise, always with people at the center. We believe that collaboration, empathy and curiosity form the foundation for achieving sustainable results. Technology must be understood and adopted to create value.
We work thoroughly and with a high level of professional discipline - balancing quality and speed. Through prototypes, close feedback and continuous adjustments, we develop AI and data solutions with both precision and momentum.
Strong solutions begin with a clear understanding of business needs and organisational direction. We start by creating clarity around business objectives, data foundations and technical maturity before deciding how the solution should be designed. Our approach is pragmatic and grounded in what creates tangible business value with Data & AI.
At Codellent, we have extensive experience developing and implementing AI solutions. We work with Machine Learning, Deep Learning and GenAI - from idea and prototype to production-ready solutions used in everyday operations. With a focus on production readiness, scalability and stability, we ensure that solutions remain reliable over time and are fully integrated into existing systems and workflows.
Advisory
Strategic guidance for execution
AI- & Data strategy with roadmaps for architecture and use-cases
Use-case scoping across personas, dependencies and cost
Architecture reviews and technical due diligence
Engineering
Building strong, scalable solutions
Data Engineering
Platform Architecture
CloudOps with DevOps, automation and integrations
DataOps, MLOps and AIOps for AI & Data lifecycle reliability
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Casper Greve
Kristian Vingaard
Anders Rosengaard
Consultant - Data & AI
Stefan Engelmann
Consultant - Data & AI
Mathias Suhr Melchiorsen
Managing Architect - Data & AI
Marcus Møller Hansen
Consultant - Data & AI
Kira Opstrup
Associate Consultant
Maybe you?
Data & AI enthusiast