AI assistants on your own data
Chat assistants that answer questions from your documents and systems (RAG), with sources, access control and quality checks.
Consultants based in Stockholm · on site or remote
AI & Machine Learning
Practical AI that saves time and improves decisions: from machine learning on your own data to generative AI assistants that work with your documents, safely and in production.
Sound familiar?
- Plenty of AI ideas, but unclear which ones are worth the investment
- Concerns about data leaks and wrong answers from AI tools
- Pilots that impress in a demo but never reach real users
What we deliver
How we can help
Document & text processing
Classify, extract and summarise contracts, invoices, e-mails and support tickets automatically.
Predictive models
Machine learning for churn, risk, quality, maintenance and other predictions, trained on your data.
AI agents & automation
Agents that carry out multi-step tasks across your systems, with people in the loop where it matters.
MLOps
Versioning, deployment, monitoring and retraining, so models stay accurate after go-live.
Responsible AI
Evaluation, guardrails and data protection, aligned with GDPR and the EU AI Act.
How we work
From idea to result
- 1
Find the right use cases
We map ideas against value, feasibility and risk, and pick the ones worth doing first.
- 2
Proof of value
A focused prototype tested on real data and real users, measured against clear success criteria.
- 3
Build for production
Security, access control, evaluation and integration with your existing systems.
- 4
Monitor & improve
We track quality, cost and usage, and improve the solution as needs change.
Typical assignments
Where this makes a difference
Internal knowledge assistant
Staff ask questions in plain language and get answers from policies, manuals and earlier cases, with links to the source.
Automated document handling
Incoming invoices, orders or applications are read, checked and routed automatically, with exceptions sent to a person.
Predictive maintenance
Sensor and service data predict which equipment is likely to fail, so maintenance can be planned instead of urgent.
Technologies we use
- Azure OpenAI
- Claude
- Azure AI Search
- Databricks Mosaic AI
- MLflow
- LangGraph
- PyTorch
- Hugging Face
- Python
Frequently asked questions
Will our data be used to train public AI models?
No. We use enterprise services, for example models hosted in your own Azure tenant in an EU region, where your data is not used for training.
Which AI model should we use?
We compare models on your own test cases and weigh quality, cost, speed and where data may be processed.
What does the EU AI Act mean for us?
We help classify your use case, document it, and put the required transparency and human oversight in place.
Let's talk data.
Tell us where you are today and where you want to go. We will help you find the shortest path there.