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Joule

Low-code use case platform designed to accelerate

business impact

Platform designed to accelerate use case delivery by reducing time to design, build, pilot and scale

Ingest
from sources

Real-time
pipeline processing

Through our low code DSL

Deliver 
streaming intelligence

Using standard or custom formats

Pre-built or custom connectors

Case Studies

Location Marketing

Use real time customer customer location data to provide location-aware marketing. Through the use of customer mobile event data, opt-ed in customers can take advantage of targeted marketing campaigns based upon their personal habits as they enter the venue

Infrastructure Planning

Optimise infrastructure capacity by applying geospatial analytics with respect to utilisation and demand. Through the use of anonymised mobile location data and historical trend modelling you can predict infrastructure capacity requirements at a point in time and therefore manage capacity dynamically

Service Dashboards

Monitor core platform services using a realtime Healthwatch dashboard feed with streaming metrics and alert signals. Edge nodes perform local window analytics (sliding/tumbling), KPIs, anomaly detection and alerting for the centralised aggregation engine and dashboard views

Customer Experience

Be alerted, be proactive and act upon customer service failures before they contact you. Build a dynamical customer experience view by correlating live service streams with historical trends and customer profiles to inform next best actions

Data Security

Addressing privacy concerns related to processing of Personally Identifiable Information (PII) is a key concern when dealing with consumer data.Through the application of a repeatable obfuscation process using event opt-out filtering, encryption and obfuscation at point of system entry demonstrates compliance adherence and facilitates multiple uses of the core data sets

Anomaly Detection

Apply advanced analytics at the edge to detect feature anomalies to achieve improved service availability. By reducing the anomaly detection latency window the ability to respond, rectify and recover cycle is shortened to the point where intelligent automation is employed

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