Autofleet, an optimization platform for fleets and transportation providers, has launched Autofleet Nova, a fleet specific large language model (LLM) powered by advanced AI to help fleet operators use plain language to gain comprehensive insights across their operations.
Harnessing AI and Natural Language Processing to Access Data and Insights
Nova was created to work on fleet domain data across a range of fleet data sources, such as demand data (trips and reservations), supply data (vehicle telematics) and infrastructure data (parking, charging/fueling, workshops etc.). This allows fleet operators to use plain language queries to gain previously inaccessible insights, identify optimization opportunities, analyze issues, and even take action.
"Nova will transform how fleet businesses operate by democratizing access to data, and by providing non-technical business and operational stakeholders with the tools to make data driven decisions" said Kobi Eisenberg, CEO and co-founder of Autofleet. "Nova’s ability to integrate data from any source and generate new contextual insights bridges the gap between different roles within the business, and empowers fleet operators to make smarter, more informed decisions and take immediate actions."
Key features of Autofleet Nova include:
Comprehensive: Integrated to any fleet data source across reservations, telematics, CRM, HR, and more giving a unified view of operations.
Context Aware: Combines previously siloed, disparate data sources to generate new fleet-specific insights, while allowing users to ask follow-up questions contextually.
Quick to Rollout: Out-of-the-box plugins enable rapid integration with most major databases including Oracle, SQL Server, PostgreSQL, Snowflake and MongoDB.
Enterprise Grade: Supports data segregation for roles and permissions.
Autofleet Nova will reach general availability in Q4 2024.
