Service
Data, AI & Automation
Turn governed data into better decisions, intelligent services, and automation that works in production.
When to engage
Make the constraint visible.
- Data is fragmented, inconsistent or difficult to trust
- AI pilots do not move into secure production
- Manual work consumes specialist capacity
Capabilities
What we bring together.
Data engineering and integration
Warehouses, lakehouses and semantic models
Business intelligence and decision support
Machine learning and advanced analytics
Generative AI and retrieval-augmented generation
Intelligent automation
MLOps, LLMOps and model evaluation
Use cases
Where the capability creates value.
Create a trusted enterprise data platform
Deploy governed AI assistants over private knowledge
Automate document-heavy operational processes
Build predictive models for demand, risk or maintenance
Delivery outputs
What you can expect to own.
- Data and AI strategy
- Governance model and use-case portfolio
- Production data pipelines and models
- Evaluation, monitoring and operating controls
Measures
How progress becomes evidence.
- Decision speed
- Data quality
- Automation hours returned
- AI reliability and adoption
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