Data-Driven Innovation Services
We are dedicated to providing a holistic approach to the
Through a combination of diverse services, we help our clients generate effective value from data and successfully navigate the ever-changing digital landscape.
Data Collection & Engineering
Data Processing & Analysis
analyses historical data to describe past events. In retail, it helps to identify successful products and adapt marketing strategies. In manufacturing, it identifies trends and potential for improvement.
predicts events using statistical models and techniques. Retail companies use predictive analytics for sales trends and stock planning. In the public sector, it helps with social services and crime forecasting for effective resource planning.
gives concrete recommendations for action for optimal results. In production: Machine settings for quality optimisation. Retail: optimal prices and stock levels. Public sector: effective crime prevention and service improvement.
AI enables personalised experiences through data-driven interactions. In retail, AI recommendation systems provide customised product suggestions based on customer purchase behaviour. Public sector: AI chatbots for 24/7 citizen access to services and information to improve the citizen experience.
AI enables intelligent, user-oriented products. In manufacturing, AI helps machines learn to improve their performance. In retail, AI-powered products like personalised shopping assistants help customers get the best shopping experience.
AI optimises and automates business processes. In manufacturing, it improves production through predictive maintenance to minimise downtime. In the public sector, AI automates application processing and better schedules services through predictive models.
Potential added value for your business
New revenue streams
AI enables the exploration of new business models and innovations through data-driven insights. New market niches and personalised offers open up additional revenue streams for companies.
Improved customer experience
AI improves customer experience through personalisation, accelerates service and enables customised products. Chatbots optimise customer service, recommendation algorithms offer tailored suggestions.
Reduction of operational costs
AI reduces costs by automating and increasing efficiency in processes. Machine learning identifies inefficiencies and predicts maintenance needs to avoid downtime.
AI increases productivity by automating time-consuming tasks so employees can focus on more valuable activities. It improves decision-making through data-driven insights and forecasts.
Increased asset efficiency
AI increases asset and infrastructure efficiency through predictive maintenance models. Maximising machine uptime and minimising energy consumption are potential benefits.
AI detects and mitigates risks through pattern recognition in data. Fraud is detected and prevented, compliance risks are reduced to meet regulatory requirements.
Our approach and services
Idea development and creation of a scenario catalogue containing the defined strategic goals, key results and prioritised scenarios
- Providing trends and insights
- Supporting the development of a vision for a data-driven future
- Definition of objectives and key results
- Identification of effective use cases
- Value assessment and prioritisation
- Roadmap development
Designing the desired state, framing the transformation journey into an actionable change programme and prototyping.
- Capability assessment and definition of the desired state related to data management, data governance, and the operating model.
- Maturity progress roadmap
- Framing the journey in an actionable change programme
- Development of the business case
- Formation of the Transformation Team
- Develop prototypes that illustrate the projected value.
Build & Operate
Implementation of the solutions and establishment of an agile governance and operating model:
- Establish a suitable agile governance model to lead the change; and
- Measuring progress
- Modernisation of the data platform
- Agile implementation of the identified use cases
- Establish the practices and services that foster continuous innovation and develop and embed digital capabilities at scale.
Typical customer project for the creation of an AI MVP
Definition of the most important tasks and goals
Identification of a business case with large scale
Value determination and prioritisation
- Objectives and key results
- High impact business scenarios
- Value analysis and prioritisation
- Scenario narratives and solution boards
- Implementation roadmap
Review of use cases & solution architecture
Data evaluation and label generation
Value determination and prioritisation
Project plan and product backlog
- Breakdown of the use case into epics, features and stories
- Solution architecture
- UX, devices, infrastructure, data sources, security and
- Analysis requirements
- Initial backlog planning
- Approval of vision and scope
- Project management
Build & Test
Data configuration (recording, conversion, etc.)
Data validation and enrichment
Data identification / labelling
Model hypothesis & architecture
Model development and testing
- Azure ML-Platform
- Environment & Data Configuration
- Cleaned & tagged/labelled data
- AI-Modell exploration & development
- Test preparation, execution and reporting
- Sprint final report
- Sprint progress demonstration
Deploy & Operate
Value Realisation Report & Leadership Presentation
Introduction of ModelOPs practices
- Model application
- ModelOPs Guide & Training
- Detailed architecture document
- Responsible AI assessment report
- Value Realisation Report
Our Envisioning the Future workshop series helps your organisation define and shape a data-driven strategy and transform your vision into a roadmap for success.
Definition of objectives and key results.
Assess the opportunities and challenges in relation to your identified business scenarios.
Identifying potential use cases for your data, designing high-level roadmaps for implementation and exploring potential partnerships and collaborations.
The Designing the Future workshops aim to develop a data strategy and execution plan that is aligned with your business objectives.
Data strategy: Define the necessary data governance to ensure quality, data protection and compliance and establish an effective data management system.
Implement by using advanced analytics and AI to scale the implementation of data-driven use cases across your organisation.
Build a collaborative ecosystem to securely share data with other businesses and expand your opportunities for collaboration and innovation.
Implement a scaling agile operating model based on the principles of SAFe, DataOps and ModelOps.
Build & Operate
Building the solutions and introducing an agile governance and operating model
- Establishing an appropriate agile governance model to lead the change and measure progress.
- Modernising the data platform.
- Agile implementation of the identified use cases.
- Establishing the practices and services that drive continuous innovation and develop and integrate digital capabilities at scale.
Register for our free workshop
Are you still unsure how artificial intelligence can be used to harness data in your company?
One of our experts will be happy to advise you in detail in a free workshop.