How RAG Models Strengthen Manufacturing Customer Support Without Replacing Human Agents

3 min read ● Silk Team

Customer support in manufacturing has its own unique challenges. Manufacturing support teams have to deal with numerous technical questions regarding equipment configuration, error codes, maintenance procedures, warranty issues, and compliance regulations. These answers need to be correct, consistent and delivered in a timely manner; however, all this data usually exists across multiple different types of documentation including technical manuals, service bulletins, engineering notes, and older legacy systems.

There are many manufacturers today that are turning to use Retrieval-Augmented Generation (RAG) models in order to help their support teams provide better customer support with less hassle and stress to both the customer and the support team.

Why Traditional Support Models Fail

While many manufacturing support teams experience similar problems:

• Long resolution times as a result of having to search through documentation
• Reliance on senior support engineers for repetitive question
• Variation in answers provided by different agents and locations
• Outdated or difficult to find documentation

Regardless of how much experience a support engineer may have, he/she still spends an excessive amount of time trying to locate information within PDF files and/or escalating cases that could have been resolved quicker if they had easier and faster access to the required information.

What RAG Provides to Customer Support

RAG models combine two main capabilities:

• Retrieval, which pulls the most relevant information from the company’s internal documentation
• Generation, which takes that information and converts it into an easy to understand and read conversational response.

Unlike other generic artificial intelligence (AI) chatbot programs, RAG uses only approved internal sources such as manuals, standard operating procedures (SOPs), service records, FAQs, etc. This will ensure that all information provided to the customer is accurate and compliant with the company’s policies and standards.

How Support Teams Actively Utilize RAG

Quick Resolution for Tier-1 and Tier-2 Support

Agents are able to immediately get answers to questions such as “what does this fault code mean?” or “what is the recommended solution for this problem?” using RAG powered tools. The purpose of this is to reduce call handling time and to eliminate unnecessary escalations.

Consistency of Responses From All Teams

All of the agents in the organization reference the same, updated documentation at all times. Regardless of who is assisting the customer or where the customer is located, the customer receives consistent responses to all of their questions.

Support for New Agents

New employees can quickly learn new products and services using RAG powered tools to assist them during live support sessions. Rather than having to rely solely on memory, new agents can learn from asking questions and referencing accurate answers to support related questions during live sessions.

Improving Escalation – Not Reducing the Number of People Involved

When a situation occurs that requires the assistance of an engineering or specialty person, RAG enables agents to collect the proper background information prior to escalating. As a result, the quality of hand-offs increases and resolution times decrease — rather than reducing the number of people involved.

Why Humans Remain Important

Manufacturing support is more than simply retrieving information. It also involves elements of judgment, empathy, and being aware of the situation — particularly when a customer’s equipment fails causing downtime, safety hazards, or costly repairs.

RAG models do not replace the human abilities described above. Instead RAG models help to:

• Decrease the cognitive burden placed on agents
• Remove the time lost looking for answers to common questions
• Enable humans to focus on problem solving and communication

Ultimately, the result of utilizing RAG models is improved customer satisfaction and reduced burn-out among support teams.

Managing Risks and Building Trust

Manufacturers are cautious when adopting RAG models and there are valid reasons for doing so. The benefits of RAG models include:

• Restricting responses to only internal documentation that has been reviewed and verified by the manufacturer.
• Ensuring that answers are updated whenever the underlying documentation is updated.
• Providing a record of origin for each answer.

Therefore, RAG models can be used in regulated industries or those requiring strict adherence to safety protocols.

The Bottom Line

RAG models enhance manufacturing customer support by empowering agents, not replacing them. By converting extensive amounts of complicated documentation into immediate, reliable answers, support teams can resolve customer issues more efficiently, support customers with more confidence and escalation when necessary.

For manufacturers committed to delivering high levels of service quality and building long term customer relationships, RAG models are not a replacement for traditional support methods but instead are complementary to them.