Introduction
BTT Engineering (BEng), a leading infrastructure and engineering solutions provider, sought to improve the efficiency of its onsite support for critical systems such as video surveillance, access control, and fire safety. Their existing manual processes were slowing response times and increasing operational costs. To address these challenges, BEng partnered with Moterra to implement a Generative AI-powered Onsite Support System that transformed their operations, enabling faster issue resolution and scalable growth.
The Challenge
BEng’s traditional onsite support system relied heavily on manual processes for resolving issues in their infrastructure services. This resulted in several challenges:
- Slow Response Times: Resolving issues in critical systems like video surveillance and fire alarms took longer than ideal, leading to potential system downtime.
- High Operational Costs: BEng required a large team of full-time engineers to manage these support operations.
- Accuracy Issues: Manual troubleshooting processes resulted in inconsistent accuracy, increasing the likelihood of rework.
The Solution
To address these challenges, Moterra implemented a Generative AI-powered Onsite Support System tailored to BEng’s infrastructure services, utilising AWS services to automate and optimise problem resolution across critical systems.
- AI-Powered Problem Resolution: Using Amazon Bedrock, the AI system generates context-aware solutions, improving response times for engineering issues in critical infrastructure systems like access control, video surveillance, and fire safety alarms.
- Automated Data Extraction from Field Documents: Using Amazon Textract, the system extracts and analyses data from engineering diagrams, blueprints, and handwritten notes, helping engineers process and solve issues faster in complex systems.
This architecture allowed BEng to improve support efficiency and scale its operations across more sites, while maintaining 24/7 availability to clients.
The Outcome
The solution led to significant improvements across BEng’s operations:
- Faster Resolution Times: Average resolution times dropped by over 50%, reducing system downtime and improving overall service quality.
- Cost Efficiency: The AI system enabled BEng to reduce the number of full-time engineers required for support, leading to substantial operational cost savings.
- Improved Accuracy: By automating troubleshooting, BEng saw a marked improvement in the accuracy of issue resolutions, minimising the need for rework and reducing material waste.
Conclusion
The adoption of Moterra’s Generative AI-powered Onsite Support System allowed BEng to optimise their infrastructure services, reduce costs, and deliver faster, more accurate solutions. This transformation enabled BEng to scale their operations while maintaining high standards of innovation and customer satisfaction.
