winter release

AI that works the way maintenance teams do

This Winter Release delivers three powerful AI-driven capabilities that enhance planning, accelerate setup, and unlock smarter insights across your maintenance operations.

Hand holding smartphone displaying an app that extracts and displays asset details like Load Center Panel, Siemens, model and serial numbers with AI extraction confidence at 100%, next to industrial electrical panel in background.
Asset Snap

Capture and identify assets instantly

Asset Snap uses AI-powered image and text recognition to extract asset details directly from a nameplate, creating a new asset in seconds.No typing. No manual entry. Just point, capture, and go.

Hand holding smartphone displaying an app that captures and confirms asset tag data with AI, showing details like Load Center Panel, Siemens, model and serial numbers, and manufacture date.
Diagram showing MCP at the center connected to AI and LLM icons on the left, with features on the right including Predictive insights, AI-driven recommendations, Smarter automation, and Faster setup.
MCP

The AI-ready data layer powering smarter insights

MCP is Limble’s new AI-ready data layer, giving developers a secure way to connect LLMs like GPT and Claude to Limble’s contextual information.

By structuring asset, work order, and operational data for AI consumption, MCP enables more accurate recommendations, faster automation, and more flexible integrations across your tools.

Resource Planning

Plan your team’s work with intelligence

Staffing decisions shouldn’t rely on guesswork. Resource Planning analyzes workloads, priorities, and labor capacity to help you schedule the right work at the right time.

See who’s available, prevent overload, and balance assignments with AI, so your team can stay efficient and focused.

Task management dashboard showing unscheduled tasks with categories for unassigned, future, and overdue tasks, and a weekly calendar with individual task assignments and remaining hours for each team member.

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