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Samsara connects real-time operational data with AI tools

The tool aims to allow companies to consult and analyze information about their operations to improve decision-making.

T21 Media by T21 Media
28 October, 2026
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The ability to consult information about vehicles , operators , safety incidents and maintenance from artificial intelligence (AI) tools opens new alternatives for the management of road transport and other activities that depend on physical operations.

From this perspective, Samsara announced the launch of Samsara MCP (Model Context Protocol) , a solution that allows connecting the operational data of its platform with artificial intelligence assistants such as ChatGPT , Claude Desktop , Microsoft Copilot and Cursor, without the need to develop custom integrations.

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The tool aims to allow companies to consult and analyze information about their operations in real time , combining it with data from other business systems to support decisions related to unit availability, operator allocation, maintenance, and operating costs.

One of the main benefits of this technology is that information is no longer only accessed within the Samsara platform and can be incorporated into the digital tools that organizations already use.

“An agent is only as useful as the context they can access, and in physical operations that context is live: where the vehicles are, which ones are out of service, who has hours left today,” explained Brendan O’Driscoll, Vice President of Platform at Samsara.

The executive noted that the addition of MCP is part of the company’s strategy to facilitate the use of operational data through artificial intelligence and automation, without requiring customers to develop additional technological connections.

According to the company, in transportation companies, the integration of operational information with AI systems can facilitate the handling of situations that require consulting different data sources before making a decision.

According to the examples presented by Samsara, in the event of a vehicle breakdown, a dispatch manager could ask an AI assistant to identify nearby operators with available service hours and then compare that information with the delivery commitments recorded in the company’s transport management system.

In terms of maintenance, the technology would allow users to consult the defects identified during vehicle inspections and use that information for an agent connected to the corresponding system to prepare work orders.

For their part, the financial areas could analyze fuel consumption along with vehicle activity and idling periods, with the aim of identifying factors that affect operating costs.

These applications are based on the integration of information that previously might have required separate queries in different systems, which represents an opportunity to streamline data analysis and reduce manual collection tasks.

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The company specified that Samsara MCP incorporates more than 40 read-only query tools , through which AI applications can access information on vehicles, operators, safety incidents, and hours of service, without modifying the original records.

Furthermore, the connections maintain the access permissions established by each organization. This means that users will only be able to access, through artificial intelligence, the information for which they already have authorization within Samsara.

Data integration for decision making

The new solution is incorporated into Samsara’s technology ecosystem , which currently has more than 400 integrations, in addition to application programming interfaces (APIs) and developer tools.

According to the company, its platform collects more than 30 billion data points annually from vehicles, equipment, and various operational activities. This information allows for the establishment of relationships between trips, operators, safety incidents, and maintenance histories.

Samsara MCP complements the Agent Center, presented during the Beyond 2026 conference, with two alternatives for organizations: developing AI agents within Samsara or connecting their operational data with external tools.

In the case of more complex queries, the connected applications can also resort to the Samsara Assistant, whose agents perform the analysis within the platform and return the results to the tool used by the client.

Regarding this integration, Ken Apple, Chief Technology Officer (CTO) of Mariner, highlighted the importance of incorporating fleet data into business processes that use artificial intelligence.

“This allows our developers to focus on solving business problems instead of maintaining another custom integration,” he said.

With this addition, Samsara seeks to expand the use of information generated by physical operations and facilitate its integration with other business management systems.

Comment and follow us on LinkedIn:  @GrupoT21
Tags: artificial intelligenceFLEET MANAGMENTfreight transportOPERATIONAL DATASamsaraVEHICLES MAINTENANCE

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índice de Confianza del Transporte y Logística – Cuarto trimestre 2023 10 destinos de exportación de vehículos pesados 2023 Descubre el Top 10 de destinos de exportación de vehículos pesados en México en 2023 La venta de vehículos pesados rompe récord en 2023 5 marcas de camiones más vendidas