Enterprise buyers are asking a new question about process mining. Beyond what the software can do, they want to know where it runs. In Part 3 of QPR Software’s CEO Interview Series, published today, CEO Matti Erkheikki argues that this question now belongs in every evaluation as AI moves into everyday operations.
“Where your software runs is no longer just a technical detail for IT. It affects how quickly you can use AI, how well you can control your data and what the solution costs as usage grows,” says Erkheikki.
According to Erkheikki, the shift is already visible in QPR’s customer conversations. Many organizations that contact QPR have built their data foundation in Snowflake and already understand process mining. Their first question is different now.
“They ask a very direct question: can we do this without moving our data out of Snowflake?”
QPR saw this coming early. In 2022 it became the first process mining software to run natively in Snowflake, and in 2024 it launched the first process mining Native App on Snowflake Marketplace. With the Native App, QPR ProcessAnalyzer is installed in the customer’s own Snowflake account. The analysis happens where the data already is, under the customer’s existing security and access controls.
Of all the benefits of native architecture, Erkheikki says time to value is the one that changes the conversation most. A conventional deployment can require new integrations, data replication and a separate security review before any analysis begins. When the process data is already in Snowflake, those steps can be skipped.
“Because there is nothing to extract and no new environment to secure, a first analysis can be delivered in hours and real value within days.”
The approach also works at enterprise scale. Ericsson uses QPR ProcessAnalyzer for global trade compliance analytics in a Snowflake environment, with more than 1.2 TB of data and 10–20 million new transactions every month.
Organizations that don’t use Snowflake can still benefit. QPR ProcessAnalyzer is available as a managed solution that runs on a Snowflake environment operated by QPR, so the customer doesn’t need its own Snowflake subscription.
Erkheikki connects the architecture to QPR’s work on making process intelligence available beyond dashboards. The QPR MCP Server uses Model Context Protocol (MCP), an open standard for connecting AI tools to business systems. Through it, people can ask questions about bottlenecks, delays and deviations in an AI assistant they already use, and get answers based on actual process data.
“Snowflake-native brings the intelligence to the data. MCP brings the intelligence to the people,” Erkheikki says.
In the full interview, Erkheikki shares seven architecture questions every enterprise should ask before choosing or renewing a process mining platform. His advice is simple: “Evaluate the architecture as carefully as you evaluate the features.”