Expertise
AI & Automation
From promising pilot to something the business actually uses.
Most organisations do not need more AI experiments. They need one process to become measurably faster, cheaper or more accurate. Our AI and automation specialists start from the business case, choose the smallest technology that solves it, and make sure the result survives contact with daily operations.
Typical challenges
- Repetitive manual work that scales badly with growth
- An AI pilot that never made it into production
- Document, email or ticket flows handled entirely by hand
- Data available in theory, unusable in practice
- Unclear where AI genuinely pays off and where it does not
Capabilities
- Automation opportunity assessment and business case
- Workflow and process automation
- LLM applications, assistants and retrieval systems
- Machine learning models and predictive analytics
- Document and data extraction pipelines
- MLOps, monitoring and model governance
- AI policy, risk and compliance guidance
Example roles
- AI Engineer
- Machine Learning Engineer
- Automation Consultant
- Data Scientist
- MLOps Engineer
Typical engagements
Automation assessment
Two to three weeks mapping where manual work actually costs money, ending in a ranked business case.
Production pilot
One process automated end to end, measured against a baseline agreed before the work starts.
LLM assistant
A retrieval-based assistant over your own documents, with evaluation, guardrails and a cost model.
What you get
- 01One process measurably faster, cheaper or more accurate than before
- 02A working system in production, not a notebook or a slide deck
- 03A cost and risk view of running the solution, including model governance
Questions about this expertise
How do you decide whether AI is the right answer at all?
We start from the business case. If a rules-based automation or a process change delivers the same result more cheaply, that is what gets recommended. AI is used where it genuinely outperforms the alternative.
What about data protection and the EU AI Act?
Data handling, retention and model governance are part of the design, not an afterthought. Where an initiative touches regulated processes, we bring in a specialist from the specialist knowledge category.
Related expertise
Software Development
Backend, frontend, mobile and platform engineers who join your team and deliver working software against a clear scope.
Operations
Operations, supply chain and process specialists who remove friction between promise and delivery.
Consultancy
Strategy, transformation and change specialists who stay until the decision is implemented.
Looking at this from a specific side? How companies engage the network · How specialists join
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