Fieldcode adds AI LLM workflow action to turn field service data into next steps

Fieldcode, a provider of field service management software, has added AI LLM actions that allow large language model prompts to run directly inside configured service workflows.

The new actions use ticket or object data already stored in Fieldcode to support tasks such as summarization, translation, data checks, field cleanup, and workflow decisions. The result can be used to update fields or support the next step in an automated process.

The feature addresses a common issue in field service operations: ticket data often contains the information needed to move work forward, but not always in a format that workflows can use immediately. Descriptions may be long, written in another language, spread across several fields, or require validation before the ticket can move to scheduling, customer communication, spare parts review, or escalation.

AI support inside configured workflows

Fieldcode's AI LLM actions are designed to run at a defined point in a workflow. Instead of requiring users to copy ticket data into a separate AI tool, administrators can decide when the action should run, which fields should be included in the prompt, and how the result should be used.

Example uses include ticket summarization, translation of customer or technician notes, phone number or address checks, customer-facing update preparation, and AI-supported movement of a case to the correct workflow step.

These actions can be used not only for tickets, but also for object-based workflows. This allows service organizations to apply AI support across different operational processes where structured interpretation of data is needed.
Administrators can configure the LLM provider and test prompts before adding them to a workflow. The first version supports OpenAI, Azure OpenAI, Anthropic, and Google Gemini.

Supporting Zero-Touch automation with better input

Fieldcode's Zero-Touch approach focuses on reducing manual handling across service intake, scheduling, dispatching, and execution. The AI LLM actions add a layer of decision support where unstructured or inconsistent data would otherwise slow down the process.

The feature does not replace configured workflow rules or operational oversight. It gives administrators a controlled way to define where AI should support the process, what data it should use, and how the output should be applied.

"AI in field service should not mean another tool, another tab, or another copy-paste step," said Matthias Lübko, CEO of Fieldcode. "With the AI LLM actions, service organizations can apply AI directly inside existing workflows, where ticket and object data already guide operational decisions. The goal is simple, help teams turn unclear service data into the next usable action faster."

Despoina Mountanea
Marketing Manager
despoina.mountanea@fieldcode.com
+49 911 99099000
Lorenzer Str. 3
90402 Nürnberg
Germany

About Fieldcode
Fieldcode is a field service management software built on 25 years of global expertise. It delivers a fully automated Zero-Touch process, automating ticket movement from creation to technician without manual intervention and easing the workload for dispatchers. The software leverages cutting-edge technology to optimize field operations, simplify processes, and improve efficiency across every stage of service management.

Links
• Fieldcode official website: www.fieldcode.com
• Fieldcode AI LLM feature: https://fieldcode.com/en/features/ai-llm-workflow-actions

This release was published on openPR.