Locus Technologies Introduces AI for Refrigerant Management

MOUNTAIN VIEW, Calif., Sept. 22, 2026 /CourierPR/ -- Locus Technologies, a leader in environmental information management and EHS compliance software, has introduced a new AI-powered image interpretation capability for its Locus Refrigerant Management applications. This technology aims to streamline the process of converting physical equipment labels and service records into structured digital data, significantly reducing manual data entry and improving accuracy.

The new AI feature allows field personnel to photograph appliance nameplates and printed service records. Locus then uses advanced multimodal AI to interpret the images, extract relevant information, and populate structured fields directly within the Locus software. For instance, a technician can photograph the manufacturer label on an appliance, and Locus will identify and map the extracted values to the appropriate fields. Similarly, the technology can interpret handwritten notes on printed service records, populating the relevant fields with the extracted information.

Each interpreted value is returned with a confidence score, providing visual indicators to help users quickly distinguish high-confidence results from information that requires closer review. This approach not only reduces repetitive work but also ensures that the resulting refrigerant records remain accurate, complete, and defensible.

The new capability is part of Locus Technologies' ongoing expansion of AI across its environmental software portfolio. Earlier this year, the company introduced LocusAI Report Agent for Environmental Information Management and expanded its AI leadership and development resources. Locus plans to bring the same photo interpretation framework to additional applications and workflows where images and documents can serve as efficient sources of structured environmental and EHS data.

Locus Technologies, founded in 1997 and remaining the longest-serving pure-play SaaS provider in the sector, serves organizations ranging from mid-size enterprises to Fortune 100 corporations. With a focus on managing environmental records, the company continues to innovate and enhance its software to meet the evolving needs of its clients.

The technology applies advanced AI to a familiar refrigerant management challenge: converting information found on physical equipment and documents into accurate, usable digital records. In one workflow, a technician can photograph the manufacturer label or nameplate on an appliance. Locus interprets the image, identifies relevant equipment information, and maps extracted values to the corresponding fields within the application. In another, the technician photographs a printed refrigerant service record, which may contain handwritten notes, and Locus extracts applicable service information and populates the appropriate software fields.

For both workflows, each interpreted value is returned with a confidence score. Visual indicators help users quickly distinguish high-confidence results from information that warrants closer review before the record is saved. The approach reduces manual data entry while keeping human validation directly within the workflow.

Behind both workflows is a reusable Locus AI architecture that can be applied to additional environmental and EHS use cases. Locus can adapt the same underlying technology by changing the instructions sent to the AI model and defining the structured information expected in return, allowing results to map directly into the appropriate Locus forms and workflows.

Locus also takes a model-flexible approach, evaluating AI models from multiple providers based on accuracy, cost, processing speed, API reliability, and other characteristics relevant to the task or the software product. Google Gemini is the initial model for Refrigerant Management software, but customers can use the Locus-recommended model, work with Locus to evaluate alternatives, or configure the technology to use a model selected by their organization.

For refrigerant management, data quality starts at the equipment. Technicians routinely work from equipment nameplates, service records, and handwritten field information, and manually transferring that information into a compliance system takes time and creates opportunities for error. AI-assisted photo interpretation can eliminate much of that repetitive entry while confidence scoring and human review help ensure the resulting refrigerant records remain accurate, complete, and defensible.

The new capability continues Locus Technologies' expansion of applied AI across its environmental software portfolio. Earlier this year, Locus introduced LocusAI Report Agent for Environmental Information Management and expanded its AI leadership and development resources. Locus plans to bring the same photo interpretation framework to additional applications and workflows where images and documents can serve as efficient sources of structured environmental and EHS data.