Kalteckorea is an industrial chemicals distributor. It specializes in high-value industries such as defense, aerospace and wind power, and many of its customers are large global manufacturers. When Kalteckorea proposes a product to these customers, the questions come first: how it differs from what they use today, and whether it meets their own specifications. The conversation starts only once the answer comes with evidence.
Kalteckorea first used Lubinpla to sell a new product line, handing it the work of finding the competitor products customers were running and comparing them on technical grounds. The team then started using it to research problems at customer sites. Today Kalteckorea keeps its customers' process data in Lubinpla.
We kept work logs and still missed things
Before Lubinpla, Kalteckorea's reps kept work logs. After a visit or a call, they wrote down what happened.
"We worked hard on our work logs and still missed a lot," says Moon Sungil, CEO of Kalteckorea.
Each rep's logs stayed with that rep. When a customer came back months later with a similar question, just finding out what had been checked last time took a long while.
Defense and aerospace customers check their own approval lists and specifications before they change a product, and they expect the same evidence from their suppliers. The reps had to gather it from scratch every time.
Competitor comparisons came first
When Kalteckorea brings in a new product line, the first question a rep hears is what makes it better than the product the customer already uses. Answering it meant finding the data on that competitor product first.
Now the rep gives Lubinpla the customer's operating conditions and the name of the current product, and Lubinpla searches the web for that product's public technical data. It adds candidates Kalteckorea does not carry and scores each one, dimension by dimension, with the evidence behind every score. Values the data does not state are marked undeclared, and the comparison also covers in-use cost by dose and change interval, and the switching procedure.
The first case was a competitor grease used by a customer that builds wind power equipment. The rep read the comparison, corrected a couple of points, approved it and took the document into the customer meeting. The customer then decided to look at a trial on the strength of that comparison.
“I can't imagine working without Lubinpla now. You could say we're hooked, and it's worth it.”
Site problems go to Lubinpla first
Once the comparisons became routine, the reps started asking about problems at customer sites too. They pass on the symptom, the process conditions, the product in use and the customer's past records, and get back the possible causes. What the data confirms, what is inferred and what is still unknown are kept apart, so the rep decides what to check first before leaving for the site.
They did that when stains appeared in an aerospace parts customer's surface treatment process. The rep worked through the checklist on site, narrowed down the cause and proposed a fix.
Customer process data now builds up in the same place. Each customer site has a project holding its process conditions, the products it uses and their quantities. When a rep reports a new reading, it is recorded with its date, and the previous value stays. Visits go into that site's work logs, with photos and analysis results attached.
Because the data comes from defense customers, the team checked security first. Data is isolated by company and not used to train AI models.
Before it answers the next inquiry, the agent reads those records.
The bigger difference was in sales
"Customer satisfaction went up, and that became our competitive edge," Moon says.
Less time spent finding data and building comparisons brought costs down. Moon still puts sales first.
"Costs went down, but the effect on sales is much bigger. When customers come to trust us, that trust turns into new sales opportunities."