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Semantic Distillation: A Brief Primer

The fact that business teams are drowning in disconnected data is getting to be a bit of a cliche. Adding a semantic layer to an enterprise data platform can bring order to chaos, allowing teams to collaborate effectively and leverage AI to unlock valuable insights.

People discussing and working together on a graph ontology
Kobai Announces Listing on Databricks Marketplace

Continuous Integration has expanded over the course of my career. 

An inexpensive, quick and easy way to build beautiful responsive website pages without coding knowledge
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RENEWABLE ENERGY FIRM

Reducing Unplanned Downtime through Predictive Maintenance
A renewable energy company aimed to minimize unplanned downtime across its wind and solar assets. By leveraging Kobai's predictive maintenance capabilities, the company enhanced equipment reliability and operational efficiency.
PROJECT
Deployment of predictive maintenance across renewable energy assets.
WHAT WE DID
Sensor Integration, Data Analysis, Maintenance Scheduling.
CLIENT
Confidential Renewable Energy Client.
TIMELINE
Start: March 2025, 6 Weeks Design, 10 Weeks Implementation.

PROJECT INFORMATION

The renewable energy firm faced challenges with unexpected equipment failures leading to energy production losses. 

Kobai implemented a predictive maintenance system that utilized sensor data to forecast potential failures and schedule timely maintenance.

CHALLENGES

  • Unplanned equipment downtime
  • Loss of energy production
  • Inefficient maintenance processes

RESULTS

40% Reduction in Unplanned Downtime
15% Increase in Energy Production
20% Improvement in Maintenance Efficiency
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Implementing Kobai's predictive maintenance has significantly improved our operational reliability and energy output.
Chief EngineerRenewable Energy Client

SCHEDULE A MEETING WITH AN EXPERT

Learn how Kobai can enhance your renewable energy operations.