Data Foundations Readiness: getting your business ready for ML and AI
Practical recommendations to help your business:
• Improve the quality of data so that it can be relied on for ML and AI solutions
• Understand the processes for governing and managing data to ensure regulatory compliance
• Create the infrastructure to make data widely available for decision-making across the business
• Highlight technical debt in your data platform that will delay the delivery of ML and AI solutions.
Want to find out more? Scroll down for our FAQs or book a call with our Data Practice Lead, Henry Brown.
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FAQs
01
Who will deliver the Data Foundations Readiness?
There will be two principal consultants, one more technically focused and the other more focused on strategy, governance, and use cases.
02
Why should I trust Crosstide to deliver this?
We have a long history of working at senior levels with client organisations to modernise engineering practices, ways of working and business strategy.
For more than a decade, we have been productionising ML solutions and have also built and delivered GenAI-based products.
Some examples include:
For more than a decade, we have been productionising ML solutions and have also built and delivered GenAI-based products.
Some examples include:
- Building the data foundations and migration to a contact centre AI solution for one of the UK's largest retailers
- Productionising complex computer vision models for a scale-up
- Building data meshes for fintech organisations.
03
How long will it take?
A typical engagement will be completed in four weeks. This time may be extended if there are a large number of stakeholders or use cases to work through.
04
What does it involve?
We will understand the short-term use cases and opportunities you are targeting. Then, we'll review the data needs for these use cases and examine the maturity of the architecture and capabilities for these products.
Your data quality processes will be assessed to ensure the quality is as high as it needs to be for sustainable business value. We'll also investigate whether any significant issues with governance gaps or processes need to be rectified (e.g. using personal data in a model hosting outside of the EU/UK).
Your data quality processes will be assessed to ensure the quality is as high as it needs to be for sustainable business value. We'll also investigate whether any significant issues with governance gaps or processes need to be rectified (e.g. using personal data in a model hosting outside of the EU/UK).
05
What will be the outputs?
- Gaps in the technical capabilities of the platform, which will impact your plans for ML and AI products
- Governance or process issues that should be considered before taking a solution into production
- Whether the data that will be relied upon is of sufficient quality for the desired product
- Remediations and rectifications to ensure products can be delivered into production in a safe and secure way.
06
What happens afterwards?
After the engagement, we can support you with implementing the remediations and rectifications identified, or we can come back and check on progress as needed.
We work alongside our clients in two ways: a project delivery mode, where we take full accountability and responsibility for delivering outcomes, or a blended mode, where we work alongside client teams to achieve the right outcome.
We work alongside our clients in two ways: a project delivery mode, where we take full accountability and responsibility for delivering outcomes, or a blended mode, where we work alongside client teams to achieve the right outcome.
