• Written by Azhar Aliyar, Director

A procurement manager reviews the purchase order table to ensure all necessary supplies are ordered for an upcoming project, but they also need to consider the security and privacy implications of using AsscherAi to query the organisation's data in natural language. This is a critical step in deploying enterprise AI security for operations, as it involves settling key questions in writing before deployment.

Processing and storage locations

The first question to settle is where the data will be processed and stored, and whether it will be used to train any models. This is crucial because it determines who has access to the data and how it will be protected. In the case of AsscherAi, the data is processed and stored on the organisation's own servers, and it does not train any models. This means that the organisation has full control over the data and can ensure that it is properly secured.

However, most people get wrong the idea that data storage and processing locations are not critical, and that cloud-based solutions are always secure. This is wrong because data storage and processing locations are critical to ensuring the security and privacy of the data, and cloud-based solutions can be vulnerable to cyber attacks.

Prompt injection as a data-boundary problem

Prompt injection is a type of attack where an attacker injects malicious prompts into the system in order to gain access to sensitive data. This is a data-boundary problem because it involves exploiting the boundaries between different systems and data sources. In the case of AsscherAi, prompt injection is mitigated by the fact that the system only queries the organisation's own data, and does not connect to external data sources.

This means that the risk of prompt injection is significantly reduced, and the organisation can ensure that its data is properly secured. A shift supervisor checks the maintenance log to ensure that all equipment is properly maintained, and this is an example of how AsscherAi can be used to query data in a secure and controlled manner.

Operations data dependencies

The operations data that AsscherAi depends on includes process and exception records, project status, budget consumption, and supplier performance. This data is critical to ensuring that the organisation's operations are running smoothly, and that any issues are quickly identified and addressed. For example, a category manager compares two suppliers to determine which one is providing the best value, and this is an example of how AsscherAi can be used to query data and make informed decisions.

The data dependencies are complex and multifaceted, and require careful consideration and planning to ensure that they are properly managed. This includes ensuring that the data is accurate and up-to-date, and that it is properly secured and protected.

What it changes about operations

AsscherAi changes the way that organisations approach operations by providing real-time insights and analysis of operational data. This enables organisations to quickly identify and address any issues, and to make informed decisions about how to improve their operations. For example, AsscherAi can be used to identify anomalies that are only visible when combining data from multiple sources, such as project status and budget consumption.

This can help organisations to identify potential problems before they become major issues, and to take proactive steps to address them. Additionally, AsscherAi can be used to track projects that are consuming budget faster than progress, and to identify areas where costs can be reduced or optimised.

Measuring the impact

The impact of AsscherAi on operations can be measured using a variety of metrics, including on-time delivery, exception rate, and expediting cost. These metrics provide a clear picture of how well the organisation's operations are performing, and can help to identify areas where improvements can be made. For example, a reduction in exception rate can indicate that the organisation's operations are becoming more efficient and effective.

By using AsscherAi to query data and make informed decisions, organisations can improve their operations and achieve better outcomes. This can include reducing costs, improving efficiency, and enhancing customer satisfaction. To learn more about how AsscherAi can be used to improve operations, visit our operations page.

Limitations and wrong choices

AsscherAi is not a solution for all operational problems, and there are certain situations where it may not be the best choice. For example, AsscherAi is not designed to replace human judgment and decision-making, but rather to provide insights and analysis to support informed decisions. Additionally, AsscherAi requires a significant amount of data to be effective, and may not be suitable for organisations with limited data resources.

In these situations, it may be better to use alternative solutions or to consult with our team to determine the best approach. To get in touch with our team and discuss your operational challenges, visit our contact page.