The Challenge: Fragmented compliance monitoring due to decentralized data sources

If you’re a utility, service provider, or logistics company that promises great service with strict SLAs, you need to make sure you’re meeting your contracts. But it’s tough because: 

• Data is in different systems: Your maintenance reports are in a database, and your contracts are in a data lake, or file storage. Standard AI tools can’t easily put this information together to give you quick answers.  

• Slow insights: Key people often don’t see maintenance problems in time. This leads to frustrating delays, fines, and missed opportunities for timely interventions before a compliance breach occurs.
• Too technical: The stakeholders who need to match an incident to a specific contract rule often don’t have the technical expertise to dig through all the systems. They end up doing this manually, by matching maintenance incidents with specific contract clauses.

Unique Solution: eRAG unites Data from Databases and Data Lake for AI Insights 

eRAG is a unique AI tool that unites all your essential information:

• Maintenance data and incident reports in data warehouses
• Contracts and related documents in the data lakes 

eRAG connects this information with the latest external context from sources like ChatGPT (for example, if a storm or workers’ strike caused the service disruption). These insights clarify if the incident is an SLA violation, in addition to deep, accurate tracking of incidents against your contracts, and performance insights into ongoing plant operations. 

Crucially, eRAG maintains existing roles and permissions so that defined access to sensitive information is upheld. 

Typical questions users ask eRAG: 

Business users can now ask ad-hoc questions and receive immediate responses. Armed with accurate data they are now able to take action at the speed of business. 

Legal teams ask eRAG: 

• What is the most common clause for breaches?

• How many contracts have been breached in Q3 2025? 

• List the incidents that violated vendor contracts and SLA using the End Date of the incident.

Operations manager ask eRAG:

• Show me the number of incidents at site number 473 in Q2 and Q3

• What was the leading cause of service disruption at site 474?

• What are the details of incident number 84608?

Why it Matters 

Companies using eRAG are already seeing significantly lower fines from SLA breaches. eRAG unites data from databases and data lakes, and collates this information with ChatGPT’s vast external information and friendly user interface. 

This gives your company better control and monitoring so you can see which fixes actually work, and identify which corrective measures are effective, and reduce the impact of failures. 

Now non-technical users can access and analyze maintenance data through an intuitive interface: 

• Compare performance metrics across different plants and components
• Identify and verify contract breaches related to maintenance issues 
• Generate detailed insights and statistics about maintenance issues 
• Automatically check for compliance, lowering legal costs and the overhead of manual reporting 

Getting started is easy 

eRAG integrates with multiple structured and unstructured data sources, with no need for pre-processing or data modeling. Initial setup involves mapping the company’s data terminology and establishing user permissions. Training focuses on query optimization rather than technical system management, with most users becoming proficient within 2-3 weeks. 

Let’s chat to see how eRAG can integrate with your environment and empower your teams with the data they need to make smart, on-the-spot decisions.