Data Science Services To Help You Deploy AI at Scale

Data Science Services

AI will provide $15.7 trillion in global economic growth by 2030, according to PwC research. And companies that can deploy AI at scale now will get the biggest share of the prize. By automating routine tasks and providing intelligent decision support to your team, AI can help your organization get ahead of your competitors.

But hiring your own team of data scientists can be a big upfront investment and finding the right talent to deploy AI in your processes can be tough. 

That’s why we’ve created the XMPRO Data Science Service. Our experienced team of AI and Data Science experts can develop bespoke AI models to suit your specific use cases.

Why Work With Us?

null

Fast Time To Value

We aim to deliver AI models that prove ROI within 6 months of deployment.
null

Easy To Scale

We can work on multiple use cases simultaneously to help you get ahead.
null

Real Industrial Experience

We understand what it takes to deploy AI in industrial and supply chain scenarios.

Use AI Models in Your Data Streams & Real-Time Apps

After developing your AI models, we can deploy them in your XMPRO Data Streams and Apps to embed them in your real-time operational processes.

null

Machine Learning

null

Deep Learning

null

Natural Language Processing

null

Computer Vision

Digital twin

Leverage The Latest Data Science Technologies in Your Real-Time Solutions 

XMPRO’s Data Stream Designer comes with pre-built connectors for a growing range of AI-related technologies, including:

null

Azure ML

null

R Script

null

Jupyter Notebook

null

IBM Watson Machine Learning

Our Engagement Model

null

Scope

your requirement by active engagement on the problem, background and business context
null

Proposal

to develop a business case for AI in your organisation with the aim to get a ROI < 6 months
null

Business Case

covering the proposed solution, costing and timing for AI implementation
null

Implement

the solution as per agreed business case and tracking of defined Key Performance Indicators
null

Optimize

to improve the solution and define requirements for future enhancements if needed

Example Use Cases for AI

Digital twin

Prescriptive Maintenance

Digital twin

Demand Forecasting

Digital twin

Fraud Detection

Digital twin

Risk Modelling