Practice · AI & GenAI
AI & generative AI consulting
AI and generative-AI consulting is the work of turning AI from an idea into a production system — choosing the use cases worth doing, proving them on your own data, and engineering them for real use with the governance, security and oversight they need.
Strategys supplies the senior specialists who do that work — as a project team or embedded in yours — so you get measurable value in production, not another proof of concept.
Who it's for
AI that has to work in the real business
The organisations that get the most from AI are the ones where it has to stand up to scrutiny — regulated numbers, audited decisions, real customers. That is where we focus: practical AI that is built to be governed, not demonstrated once and forgotten.
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Financial services
Banks and insurers applying AI to risk, compliance, fraud and customer analytics under governance and operational-resilience expectations such as the EU DORA regulation.
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Life sciences
Pharma and biotech teams putting machine learning and generative AI to work on research, clinical and operational data in regulated environments.
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Public sector & industry
Public institutions and manufacturers that want dependable, auditable AI in the flow of work rather than isolated experiments.
How we work
From strategy to production, one use case at a time
We move a use case from framing to production with the value defined up front and the model measured against it. Reliable AI rests on reliable data, so where the foundation is the blocker we address it as part of the work — often alongside our data and Databricks practice.
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Frame the use case and the value
Start from a business problem, not a model. Agree what good looks like, the value at stake and the guardrails, so we build AI that someone will actually rely on.
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Assess data and feasibility
Check that the data, access and quality exist to make the use case work, and choose the right approach — classical machine learning, retrieval over your own content, or a generative model — for the job.
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Build and evaluate
Develop the solution against a clear evaluation set so accuracy, safety and cost are measured, not assumed, before anything goes near production.
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Productionise and govern
Engineer the system for real use — monitoring, human oversight, access control and an audit trail — so it meets security, privacy and EU AI-governance expectations.
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Enable and scale
Hand over documentation and ways of working, upskill your team, and set up the pattern so the next use case is faster than the first.
Experience
Senior specialists, not slideware
Every consultant we place is a senior specialist who can both shape the strategy and build the system. We work across financial services, life sciences, the public sector and manufacturing, with senior specialists who bring both Danish and international experience.
FAQ
AI & generative AI — questions we get
What does an AI and generative-AI consultancy actually do?
We take AI from strategy to working software. That means helping you choose the use cases worth doing, checking the data and feasibility, building and evaluating the solution, and engineering it for production with the monitoring, oversight and governance it needs — rather than leaving you with a demo that never ships.
What is the difference between AI and generative AI?
AI is the broad field of systems that learn from data, including the classical machine-learning models used for prediction and classification. Generative AI is the newer branch — large language and multimodal models that produce text, code, images or structured output. We work across both and pick whichever fits the problem; often the best solution combines them.
How do you avoid AI projects that never make it past a proof of concept?
We frame each use case around a business outcome and a measurable evaluation from the start, and we plan for production — data access, monitoring, human oversight, security and governance — before building. That is the difference between an experiment and a system people trust, and it is why we describe our AI work as strategy to production, not proofs of concept.
How do you handle governance, security and the EU AI Act?
We build AI to be governed: access control, data-protection by design, human oversight, evaluation and an audit trail, aligned with GDPR and the EU AI Act. The specific controls depend on the risk of the use case, and we design them in from the start rather than bolting them on later.
Do you need a Databricks or modern data platform first?
Not always, but reliable AI needs reliable data. Where the data foundation is the blocker we address it as part of the work or alongside our data and Databricks practice. Where the data is already usable, we can move straight to the AI use case.
Can we engage Strategys as embedded specialists or as a project team?
Both. We supply senior AI and data specialists either embedded in your team as staff augmentation, or as a project team that owns delivery end to end, working across Denmark and the Nordics in Danish, English, Arabic, Urdu and other European languages.
Have an AI use case you want in production?
Tell us the problem you are trying to solve. We will talk you through whether it is ready, what the data needs to look like, and how we would build it to last.
Contact us