Solutions
Customer challenges
These are the key problems we are typically brought in to work on. Sometimes it involves one topic in isolation. Other times it involves supporting a holistic DAIR journey.
Lack of holistic approach to address DAIR barriers:
Lack of in-house examples:
Inspirational lighthouse projects in commercial business operation.
Lack of data literacy:
Data-and-AI savviness among legacy domain leaders and experts.
Lack of expertise:
Sourcing and orchestration of expert talent and resources.
Lack of structural capital:
Data-and-AI–Ready ways of working, operating model, data, technology stack, and governance structures.
Lack of human capital:
Culture of innovation, enterprise-federated community-driven sharing and harvesting, and agile cross-functional teams.
Lack of scaling engine:
Creating perpetual innovation and optimisation with a D&AI industrialisation and scalability muscle. Continuously growing the D&AI DNA inside the organisation.
Lack of holistic approach to address DAIR barriers:
Lack of in-house examples:
Inspirational lighthouse projects in commercial business operation.
Lack of data literacy:
Data-and-AI savviness among legacy domain leaders and experts.
Lack of expertise:
Sourcing and orchestration of expert talent and resources.
Lack of structural capital:
Data-and-AI–Ready ways of working, operating model, data, technology stack, and governance structures.
Lack of human capital:
Culture of innovation, enterprise-federated community-driven sharing and harvesting, and agile cross-functional teams.
Lack of scaling engine:
Creating perpetual innovation and optimisation with a D&AI industrialisation and scalability muscle. Continuously growing the D&AI DNA inside the organisation.
Case studies
Data mesh architechtureand data engineering
Global truck and bus manufacturer
In this case, Dairdux shaped and supported a DAIR transition. The starting point was the client’s technology-focused on-prem central monolithic data lake managed by IT. The result was a new Data Mesh architecture focused on business-domain-driven federated data, DataOps practices, and organisation in the cloud.
DAIR transformationand interim management
Global loan, leasing and insurance provider
This case was about digital repositioning of organisation, roles, ways of working, operating model, and tech stack to be relevant in the emerging FinTech ecosystem and to be future-proof with regards to growing regulatory demands.
Dairdux took the role of a global interim manger to establish ways of working and to grow a self-sufficient team to establish data-, analytics-, and insights-driven practices. The result is a ”Data-and-AI Readiness Engine” that includes agile and lean start-up portfolio steering, business solution ownership, as well as technical DevOps of data products according to Data Mesh, using the latest big data technologies.
Data/AI readiness due dilligence
Mining
In this case, Dairdux performs a DAIR due diligence with the purpose of aligning key experts and stakeholders towards a common analysis of key issues. We identified prioritised focus areas with a concrete actionable backlog and approaches to start executing on this backlog in a pragmatic, agile, and accelerated way.
DAIR crossfunctional process design
Global pump manufacturer
In this case, Dairdux’s engagement was to address the inherent challenge of working effectively through the use-case life cycle as a multi-disciplinary team. This was required to put data-, analytics-, and AI-driven services in production with full business adoption. This allowed the client to balance agile fast results in a single use case with growing enterprise D&AI capability. The outcome was the conception and adoption of the AIRPLANE philosophy and framework.
DAIR crossfunctional process design
Global power plant developer
In this case, the issue was their MVP Customer Demonstrator of digital analytics services for optimisation of their power plant operations, condition monitoring, and predictive maintenance that was conceived in their innovation lab.
Dairdux secured that the solution could be effectively disseminated into relevant functions in the organisation to reach commercial production, and in a globally repeatable and scalable way. The objective was to achieve accelerated speed from idea to commercial production for a digital analytics innovation portfolio.
Why Dairdux?
By now, it is a known fact that D&AI, and the infrastructure it runs on, is becoming a core piece of any business or process.
Dairdux is not here to help you put D&AI on top of your proud analog legacy, but rather to reinvent your core ways of working, your tech stack, and your organization with D&AI first in mind.
To successfully infuse your legacy domain expertise with D&AI software capabilities, you need to work with the best of the best, covering many different facets orchestrated as a D&AI industrialisation journey.
That is why Dairdux is organised as a consortium of experts in their field working to guide and supplement our clients D&AI industrialisation journey.
What do we work with?
Dairdux focuses on the key ingredients to succeed with a DAIR transformation. To reach an industrialised DAIR operation and to put D&AI–driven services in production.
DAIR transformation,
navigation
and orchestration.
D&AI architecture
and engineering.
DAIR Business Solution
Owner and
AI-augmented UX.
Data science
AI algorithm owner
and ML ops.
DAIR transformation,
navigation
and orchestration.
D&AI architecture
and engineering.
DAIR Business Solution
Owner and
AI-augmented UX.
Data science
AI algorithm owner
and ML ops.
When do you want to work with Dairdux?
When you are ready to go from talking and piloting to start doing it for real
When you are ready to go from high-level executive PPT to a DAIR implementation of your operating model and ways of working.
When you are ready to translate your strategy and ambitions in data, analytics, and AI into an operational vision and strategy execution.
When you want to make data, analytics, and AI an integral part of your core operations and ways of working.
DAIR to make AI work! And in a sustainably industrialised way.
Who do we work for?
We work with clients who are set on building capabilities that are relevant in a D&AI-first society.
We navigate intersectional change and innovation by being experts in the Data-, AI-, and cloud-first technology stack and in the ways of working with and governance of federated data. This will be the new normal for the D&AI ecosystems underpinning the emerging ecosystems in Energy, Transport, Water, Public Sector, Patient and Health, 5G/IOT/Communications, Media, and FinTech.