Scaling order intake without scaling headcount: how Oatly automates manual order channels with GeneralMind
About Oatly
Oatly is the world’s original and largest oat drink company. Founded in Sweden on the basis of research at Lund University and headquartered in Malmö, Oatly offers a broad portfolio of dairy alternatives, from oat drinks to ice cream, yogurt, and cooking creams. The brand is available in more than 50 countries and generated roughly $860m in revenue in 2025 with around 1,400 employees.
Oatly grew extremely fast from a challenger brand into the global category leader. As the company matures, profitability has moved into focus: improving margins is a strategic priority, which puts operational efficiency across the order-to-cash process center stage.
Use-case definition
The focus is Sales Order Processing: reading, structuring, and completeness-checking of orders that arrive through manual channels in multiple languages and formats, followed by booking into the ERP. GeneralMind handles this variability reliably and escalates open questions instead of letting incomplete orders slip through.
The challenge
A substantial share of Oatly’s incoming order volume, more than half, does not arrive through structured channels such as EDI or automated interfaces, but through manual channels, above all email inboxes.
Before GeneralMind, employees speaking various languages handled these orders entirely by hand:
Receiving each order and checking it for completeness.
Raising queries with the customer whenever information was missing.
Transferring the completed order into the ERP for further processing and dispatch.
This manual, repetitive work is slow and costly at scale, and it sits in direct tension with the company’s margin targets.
The solution
GeneralMind was deployed exactly at this interface between unstructured inbound orders and the ERP. The solution drastically accelerates the process and automates it with the Autopilot, so that order capture now runs fully automatically and in some cases autonomously. The system is especially powerful because it can fuzzily match and structure SOs from incomplete information through an AI-Fuzzy-Match.
Fuzzy match
GeneralMind handles unstructured and incomplete information through fuzzy match against master-data, saving operators tremendous time.
Human in the loop
Where needed, staff review proposed orders and can adjust, correct, or refine them quickly and intuitively.
Confidence score
Where the AI is confident, the Autopilot executes the action autonomously.
Expert judgment stays with the team, while the Autopilot handles order capture — running partly, and often fully, automatically.
Results / Impact
Quantitative wins:
Qualitative wins:
