AI & Machine Learning
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AI & Machine Learning

Build AI systems that actually work in production not just in notebooks.

Build intelligent systems that learn, predict, and automate from LLM integration to custom ML pipelines.

Veritaz AI & Machine Learning services help Swedish organisations move from AI experimentation to production-grade intelligent systems. Our team of ML engineers and data scientists has hands-on experience across the full AI lifecycle from problem framing and data preparation to model training, evaluation, deployment, and monitoring. We work with both open-source and commercial LLMs, and we understand the EU AI Act and GDPR implications of deploying AI in regulated industries.

Key Benefits

  • Production-grade AI, not just proof-of-concept demos
  • Experience across LLMs, computer vision, and forecasting
  • EU AI Act and GDPR compliant by design
  • MLOps infrastructure for monitoring and retraining
  • Measurable business outcomes, not just model accuracy
  • Knowledge transfer your team learns as we build

What's Included

LLM integration & fine-tuning
Custom ML model development
RAG & knowledge base systems
Predictive analytics

Our Process

A clear, structured approach from first conversation to delivery.

1

Problem Framing

We start by identifying the right problem to solve with AI. Many projects fail because AI is applied to the wrong problem. We help you frame the use case in terms of business value and technical feasibility.

2

Data Assessment

We assess your data availability, quality, labelling requirements, and privacy considerations. This determines the feasibility and approach for your AI solution.

3

Model Development

We develop and iterate on models using the most appropriate approach fine-tuned LLMs, classical ML, or deep learning validated against your business metrics, not just benchmark scores.

4

MLOps & Deployment

We deploy models with a full MLOps infrastructure: model registry, serving layer, A/B testing, drift monitoring, and automated retraining pipelines.

5

Governance & Compliance

We document your AI system for EU AI Act compliance, implement explainability where required, and set up audit logging for regulated industry use cases.

Technologies & Tools

PythonPyTorchTensorFlowscikit-learnHugging FaceOpenAI APIAnthropic ClaudeLangChainLlamaIndexMLflowKubeflowSageMakerPineconeWeaviateRay

Frequently Asked Questions

Do you work with open-source LLMs or commercial APIs?
Both. We recommend the right approach based on your cost, latency, data privacy, and control requirements. For sensitive data, we often recommend open-source models deployed in your own infrastructure.
What does a typical AI project engagement look like?
A typical engagement starts with a 2–4 week discovery and prototyping phase to validate feasibility, followed by a 8–16 week build phase for production deployment. Timelines depend heavily on data readiness.
How do you handle GDPR when training on customer data?
We design data pipelines with privacy by design pseudonymisation, data minimisation, and appropriate retention policies. We also provide DPIA support for AI systems that process personal data.
Can you help us evaluate whether a use case is suitable for AI?
Yes. We offer AI readiness assessments a structured evaluation of your use case, data, and organisational maturity that gives you a clear recommendation before committing to a full build.

Ready to get started?

Talk to our team about how AI & Machine Learning can help your business.

Book an AI Consultation