GE Digital Ghost - Embedded IoT & Kibana Analytics

Stabilized GE's Digital Ghost C++ system and built custom Kibana React plugins for real-time Elasticsearch data access and advanced analytics

General Electric Global Research partnered with TaylorMade Software to enhance the performance and observability of their Digital Ghost embedded monitoring system, used for real-time power grid telemetry in high-demand environments like NYC's Con Edison.

We identified and resolved persistent C++/C memory leaks in GE's proprietary memory pool libraries using Valgrind and GDB, stabilizing long-running embedded workloads.

On the analytics front, we developed a custom Kibana plugin in React and Node.js that streamed in-memory data and exported Elasticsearch datasets using elasticdump, via an intuitive Query-By-Example (QBE) UI.

Our enhancements to Kibana's UI and service layer enabled new index field creation with metadata tagging, which significantly improved search, filtering, and dashboard insights by 25%.

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