United StatesTechnology and telecom2026 – ongoingEnsono
Machine learning engine and AI diagnosis tool for IT incident resolution
Ensono cut incident resolution time by 54% when its machine learning engine flagged major incidents
Problem
Ensono runs IT systems for clients and had to find and fix service-impacting incidents fast. Support tickets arrived in large numbers, and it was hard to tell early which ones would grow into major incidents.
Approach
Ensono built the Envision Predictive Engine, a machine learning model that estimates how likely each support ticket is to become a service-impacting event. It then built DiagnoseNow with Snowflake Cortex AI and Streamlit. The tool runs root cause analysis and gives engineers a resolution plan. A pilot study tested DiagnoseNow on incident resolution.
Results
Takeaway
Early warning on tickets and AI-guided diagnosis worked on different parts of the same problem. The prediction engine cut resolution time, and the diagnosis tool cut the number of major incidents.
Categories
- Industry
- Technology and telecom
- Business function
- IT and R&DProduction and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLGenerative AI
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Snowflake describes how Ensono uses a machine learning engine and a Cortex AI diagnosis tool to handle IT incidents. It reports a 54% lower resolution time when the engine proposed major incidents and 22% fewer major incidents. The page carries no date; the Internet Archive first saved it on May 18, 2026.
Full details are in the original sources.