Agentic AI That Turns Field Signals Into Service Action — Meet Tavant at Field Service Next West 2026
Your team is already sitting on a goldmine of field signals — IoT alerts, asset history, technician notes, parts data, work orders, warranty claims. The problem was never data. It’s the gap between signal and action. That gap costs service organizations millions every year in unnecessary dispatches, repeat visits, and SLA failures. Join Tavant at Field Service Next West 2026 and see how agentic AI closes that gap across the entire service lifecycle.
AI Advisory Lab
Proof of Concept Presentation
AI Advisory Lab
Personalized Discussions
Live AI Agents Demo
For end-to-end Service Lifecycle
What We’re Bringing to Field Service Next West 2026
From Signal to Action: Agentic Field Service Intelligence
Most field failures send detectable warnings 24 to 72 hours before they happen. Tavant’s SLM AI Agents read IoT telemetry, usage patterns, and service history and act before your customer picks up the phone. Your technician arrives with answers, not questions.
First-Time Fix Is a Data Problem
Right technician. Right parts. Right route. AI makes this call in seconds, matching skills, location, parts inventory, and asset history simultaneously. Fewer repeat visits. Higher CSAT. Lower cost per case. Before the van leaves the depot.
SLA Compliance Starts Before the Ticket Opens
Reactive scheduling is a losing game. Intelligent dispatch, AI-guided triage, and prescriptive service steps compress resolution time at every stage, delivering faster resolution, stronger SLA performance, and happier customers.
AI Agents for Every Role. Always On.
Tavant SLM AI Agents help OEMs, suppliers, dealers, distributors, and customers accelerate transformation across your end-to-end service lifecycle, from first signal to final resolution with Field.AI · Warranty.AI · Knowledge.AI · Quality.AI · Contract.AI · Price.AI · Connect.AI
AI Advisory Lab
Cost-per-Case in Field Service
Session 1: AI Advisory Lab: Proof of Concept Presentation
Date: Tuesday, April 7 | 12:20 pm PT
Session 2: AI Advisory Lab: Personalized Discussions
Date: Thursday, April 9 | 11:00 am PT