Put AI to work across your organization
Without a solid foundation, even the most advanced AI initiatives will fail to deliver meaningful results. We take you through four steps: assess, plan, build and support.
- Assess: landscape, challenges, objectives.
- Plan: milestones and priorities.
- Build and iterate: in cycles.
- Support and improve: monitoring and refinement.
- Feedback at every stage, in the third step.
- Knowledge transfer to your team, after the fourth step.
Where does your foundation have gaps?
Mark the areas you already have in place. The rest are where the work starts.
Tap an area to mark it in place.
Weak foundations slow AI down
Data is the most strategic asset of any organization. Yet many businesses struggle with fragmented data landscapes, poor data quality and slow insight.
Weak data infrastructures damage credibility and slow development.
- Weak infrastructure that slows development. Service area: Data Foundations. Scalable, governed systems that fix weak infrastructure.
- Insight that does not arrive at speed. Service area: Analytics & Insights. Self-service reporting that gives decision-makers actionable intelligence.
- People and process gaps. Service area: Digital Operating Model. Identifies people and process gaps, designs new models, builds capabilities.
Each problem has a service area. The first step, assessing your landscape, is where we find them with you. Follow the four steps
How the parts fit
Two services carry the work. Strategy + Innovation aligns digital initiatives with business objectives. Data + AI puts your data to work, from analytics to automation.
- Strategy + Innovation: align digital initiatives with business objectives. It holds the Digital Operating Model: identifies people and process gaps, designs new models, builds capabilities.
- Data + AI: put your data to work with AI and machine learning. It holds six areas.
- Data Foundations: scalable, governed systems that fix weak infrastructure.
- Analytics & Insights: self-service reporting that gives decision-makers actionable intelligence.
- Data COE & Enablement: data, AI and analytics operations, centralized to speed up decisions.
- Data Products: customized solutions for specific business needs, built within your environment.
- AI & Machine Learning: intelligent automation for better decisions and operations.
- Generative AI: advanced language processing, such as advanced search or next-generation chatbots.
Where it fits, we work with our own tools:
- Sophon (opens in a new tab)AI agents that run real workflows across your stack.
- DatarootAnswers from your data, in plain English.
How we work with you
Four steps, from assessing your landscape to passing knowledge to your team.
Assess your landscape
Review your current landscape, challenges and business objectives.
Plan your roadmap
Craft a roadmap with clear milestones and priorities.
Build and iterate
Deliver in cycles, with continuous feedback loops at every stage.
Support and improve
Monitor, refine and pass knowledge to your team.
Questions before you start
Is this mainly a tools question?
Not only. Technology is one part. People, processes and strategy have to work together with it.
Where do we begin?
With the first step: a review of your current landscape, your challenges and your business objectives.
How does the work run?
Against a roadmap with clear milestones and priorities, delivered in cycles with feedback loops at every stage.
What happens after delivery?
The fourth step covers ongoing monitoring and refinement. It also passes the knowledge on to your team.
Tell us whereyour AI work stands
Starting your data journey or scaling AI across your enterprise, tell us what you need.