The job ends, then the paperwork starts
Technicians finish the real work and then reconstruct notes, parts, photos, customer promises, time, and next steps later—often from memory.
FIELD SERVICE · SIMPLE MODE
AI for field service that follows the work instead of creating more work.
INTIGNAI Field is built for mechanics, installers, technicians, contractors, network crews, and owner-operators who need less admin—not another software course. Capture what happened once, let AI prepare the connected computer work, and keep consequential execution under control.
THE OPERATING PROBLEM
The highest-value automation often starts after the physical work: documentation, handoff, follow-up, scheduling, materials, and customer context.
Office and field truth drift apart
Schedulers, owners, customers, and technicians each hold part of the story. Missing context causes callbacks, repeat questions, bad handoffs, and work that gets entered twice.
Most software asks the worker to become a software operator
A useful field system should accept voice, photos, short updates, and obvious actions while the deeper structure, memory, and policy stay underneath.
CONTROL BEFORE AUTONOMY
The interface can be simple without making the underlying operation shallow or uncontrolled.
Capture once at the source
A field update can become durable job context for notes, parts, equipment, customer history, follow-up, and the next office action instead of being retyped into multiple systems.
Simple surface, deep system
Crews can use a minimal mobile-first interface while managers retain the fuller workflow, evidence, approvals, customer context, and operational visibility they need.
Govern the side effects
AI can prepare work freely, but customer sends, account changes, infrastructure mutations, purchases, deletes, or other consequential actions remain bounded by explicit authority.
VERIFY IT
Start with one annoying repeat task from a real workday.
Describe the work in plain language. The first map focuses on what gets repeated, what information already exists, what AI may prepare, what still needs a person, and what outcome would actually save time or recover revenue.