MRPeasy Integrated Google Gemini for Data Queries
The manufacturing software provider added an AI assistant to handle natural language requests for operational reports.
Updated on Oct. 7, 2026 in Artificial Intelligence
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MRPeasy has launched a new AI assistant called Mr. Peasy, powered by Google Gemini, which allows users to query operational data using natural language. This feature is now available for production, inventory, and supplier report generation.
Why it matters
The tool streamlines data retrieval for non-technical users in manufacturing environments, reducing the time spent navigating complex software interfaces. By automating report generation, the company aims to simplify information access for new employees.
The system processes natural language queries via a commercial Google Gemini API. While it can generate charts and tables from internal data, it operates strictly in read-only mode and is disabled by default.
The players
MRPeasy
A provider of enterprise resource planning software based in Dallas that manages production, inventory, and supply chain data.
A multinational technology company providing the underlying Gemini large language model infrastructure via commercial API.
The details
The integration relies on a data-scrubbing architecture where sensitive information is replaced with random identifiers before being sent to the Google Gemini model. This mechanism ensures that user prompts and model responses are not utilized for further training of Google's AI models. Access is strictly governed by account administrators, who must manually enable the feature before users can generate reports.
Timeline
October 7, 2026: The AI assistant features were officially introduced.
The Tech Race
The rollout follows a broader industry trend of integrating generative AI into specialized ERP platforms to enhance business intelligence workflows. MRPeasy aims to compete with larger, legacy operational software suites by lowering the barrier to entry for complex data analysis.
Dallas-based users and other customers can now generate operational charts by querying their own data directly through the assistant. To utilize this, account administrators must actively enable the feature, which defaults to an off state for security.
The takeaway
This update demonstrates a shift toward using natural language models to extract complex data from legacy manufacturing tools without risking data privacy. Watch for future performance benchmarks regarding how these AI-generated reports compare to traditional database query times.
Further reading
Explore more about how large language models are transforming enterprise workflows at our Artificial Intelligence section.
More information
For more details on the assistant capabilities, visit the MRPeasy product information website.
Source note: This article includes information reported by Manufacturing.
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