project44 has integrated its Mo AI supply chain analyst with Snowflake Cortex AI, giving logistics teams a way to query operational data in natural language. The system is intended to connect questions directly with customer-specific business definitions and underlying shipment records.
Mo interprets a request before retrieving data and recommending action. That process is important because measures such as on-time performance can vary according to transport mode, contract terms, milestones and the point at which transit time begins.
The integration uses project44’s logistics ontology, semantics and network data, including approximately 1 trillion shipment records collected over the past decade. Cortex Analyst converts Mo’s interpreted requests into SQL and retrieves results from project44 data in Snowflake. Details are available through project44’s Mo solution.
Project44 reports that Mo answered 10 out of 10 verified questions correctly in internal testing, compared with two out of 10 for a general-purpose large language model. It also returned consistent answers across 10 repetitions and was 2.5 times faster. The platform is now used by 210 customers and has answered more than 50,000 questions.
Reported customer outcomes include a $6 million reduction in detention and demurrage exposure, $200,000 released from working capital through one query and nearly $750,000 saved through a disruption-management initiative. The companies position the integration as a way to make supply chain analysis faster, more repeatable and accessible beyond specialist data teams.
