At Purview, we help businesses digitize frontline operations. Our mission is to improve the quality of the end product that our customers deliver to their customers.
Generative AI is very relevant to this mission, but specific use cases are still unclear.
I made this list as a thought experiment: how might our customers be using LLMs in the next 2 years?
Image review
When an employee is responsible for a physical space or product, it’s common to take photos for QA or proof of work. These images are sometimes reviewed for quality. LLMs can perform image review, so every image is inspected for quality standards.
- This can also apply to video.
- Taken to its limit, this can provide a full guarantee of product quality.
Remote auditing
Most frontline environments have camera feeds, and these are often audited from a central location. LLMs can perform remote audits. This
Issue automation
Employees often have software systems for reporting problems, which are triaged and then addressed by others in the organization. LLMs can triage issues, reducing TTR and management overhead.
Customer communication
Many businesses ask for customer feedback on an order. For high value products, this feedback is often gathered from a human in a customer success role. LLMs can communicate with customers to build customer relationships. .
Order customization
Suppose you are preparing a salad on a line, and you see an alert “make sure to only use moist chicken for this customer”. This usually requires a specific request from the customer, and coordination between systems. By reviewing disparate customer data, LLMs can customize orders automatically.
Coaching
Coaching opportunities is one of the primary functions of a manager, but it’s time consuming and the coaching itself is error-prone. LLMs can automate employee coaching.