Case Study
60% cost optimization using AI to enable preventive maintenance for a multinational oil and gas company
- Industry: Energy (Oil & Gas, Renewables)​​
This multinational oil and gas company is among the world’s largest companies out of any industry. This $381 billion company has over 86,000 employees worldwide and a presence in more than 70 countries.
Challenge
A large global oil and gas company set a target to prevent leakages due to corrosion and plant downtime to zero by 2030. Manual inspection of pipelines’ integrity for failure signals has limitations:
- Time-consuming
- Less responsive
- Error-prone
- Non-scalable
Solution
We developed an AI application to synthesize and process drone images using computer vision to detect, classify, and provide early warning triggers for pipeline corrosion, and asset health driving preventive maintenance.
Tech stack
Outcome
70%
Manual inspection effort reduction.
60%
Optimization of cloud computation cost.
Reduced HSE incidents and minimized environmental hazards.
