The challenge
Sarlin's service-contract pricing ran on manual Excel work and the institutional knowledge of a few senior experts - accurate in their hands, but slow, hard to scale, and difficult to apply consistently across a large and varied equipment base.
Pricing by hand, one spreadsheet at a time
Maintenance contracts were priced manually in Excel. The process was time-consuming, easy to get wrong, and hard to scale as the equipment base grew - every quote started close to scratch.
Knowledge locked in a few heads
Cost estimates leaned on the intuition of senior experts rather than structured history. That made pricing hard to standardize across the team and difficult to teach to new people.
Equipment data too fragmented to automate
The records needed to automate pricing were incomplete and inconsistent - the same component could appear under many different names, and key technical details were missing. Without clean, structured data, no pricing logic could be trusted.
What we built
We built a working pricing engine in two layers: an AI-powered tool that cleans and enriches the equipment data, and machine-learning models that turn that data into a defensible price - all behind a secure web app account managers actually use.
Results
Sarlin moved from manual, intuition-based spreadsheets to objective, repeatable pricing - delivered as a working tool, not a slide deck. The same logic now applies consistently across more than 1,500 devices.
More than 1,500 industrial devices, once scattered across inconsistent records, were standardized into a single governed register that the pricing engine draws on for every quote.
Around 312,000 historical ERP transaction records were cleaned and analyzed to train the models - turning years of dormant data into a pricing asset.
Separate models for material, labor and travel costs feed an integrated total, so each quote breaks down into drivers a manager can see and defend.
Pricing no longer depends on who is in the room. The engine replaces manual Excel guesswork with repeatable logic - and shows the cost history behind every number, so teams can trust and explain it.
