Solution · Specialty chemicals
Capturing application engineering knowledge and putting it to use
In specialty chemicals, the knowledge needed to answer many technical customer questions often sits with a few long-serving application engineers. Together with them, we capture this knowledge and link it to your data sheets and test reports.
In daily use at our clients
Specialty chemicals manufacturerSales asks an AI agent technical questions and receives answers from the company's own documents.Is our adhesive K-240 resistant to continuous contact with diesel fuel at 60 °C?
Is there test data or an earlier customer case at 60 °C?
The starting point in specialty chemicals
- 01
Experience held by a few people
In many companies, only a few people in application engineering know which formulation suits which application and how earlier customer cases were solved. This usually becomes apparent only when a retirement approaches or new colleagues need to be trained.
- 02
Technical questions in sales
When a customer asks whether a product is suitable for their application, sales first looks for the answer in data sheets and earlier emails. Anything that cannot be found there goes to application engineering, which handles such requests alongside its day-to-day work.
Use cases
How the knowledge is captured and used
In conversations with your experienced application engineers, we record which questions come up regularly and where the answers can be found today.
- 01
Capturing the experience of application engineering
What is recorded in these conversations is combined with your data sheets, test reports and formulations into one shared knowledge base.
- 02
AI agent in sales
Your sales team asks the agent technical questions, for example about a product's resistance, and receives the answer from your own documents.
The goal is for sales to answer recurring technical questions on its own. How well this works shows in the number of requests that still go to application engineering.
- 03
AI product advisor on your website
Visitors to your website describe their application, and the product advisor suggests suitable products based on your knowledge base. Which content the advisor may share externally is agreed with you in advance, so that confidential information such as formulations stays internal.
Above all, a project like this needs time from your application engineers, first for the conversations and later for reviewing the first answers. It also requires access to data sheets and test reports and, where you approve it, to formulations.
On our platform, your documents are neither used to train language models nor stored by the model provider.
Platform and your own IT compared→