Mobile-first, data driven products

Experienced with integrating into legacy backend systems like banking systems, retailer transactional systems, sensor databases, etc.

Experienced at building API's for both mobile and web frontends.

Industry examples

Insights from data generated by connected devices and sensors through machine learning and useful visualisation of the data

Examples :

Optimising preventative maintenance through machine learning model on data from machine sensors
Prediction of worker and customer behaviour through machine learning on measured data
Prediction of health outcomes and risk factors using machine learning on health metrics from wearables and other health devices
Mobile interface between wearables sensors and the user
Interface to medical devices

Examples:

Prediction of sales, stock levels and staffing requirements from transactional data through machine learning
Visualisation of useful insights from financial and transactional data
Interaction channels for clients of financial institutions that are much more convenient, faster and simpler than traditional interaction channels

Examples:

An automated system for monitoring the movement of assets, reducing the time it takes to keep track of assets and their location.
An app based tasking system where employees are given the relevant tasks depending on their location and context. Gives workers the relevant information to make them more productive, and allows real time feedback of productivity and compliance.
SOLA : reducing the time to produce reports
Hungry Lion: Dashboard highlighting problems, allowing timely intervention and saving costs.
Machine learning to predict more efficient ways to employee assets and people to established processes.