We built a multimodal AI assistant for field technicians. They ask questions out loud, upload equipment photos, check service history and get troubleshooting guidance, without stopping work to search through manuals.
Industry: Logistics & Field ServicesService: AI & AutomationUpdated
Overview
The challenge
Technicians relied on equipment manuals, past service notes, customer history, photos and troubleshooting guides. The hard part was getting to that information while standing in front of the machine.
Typing long notes or searching manuals on a phone slowed every job down. The company wanted technicians to be able to talk and show, using voice and images, as part of the normal workflow.
Technicians spent time searching documents while the customer waited.
Manual notes varied in detail and quality from one technician to the next.
Newer technicians often had to phone experienced colleagues for help.
The solution
The mobile assistant takes photos, voice notes, equipment details and service context in one workflow.
The AI combines the photos with technical knowledge and the equipment's service history to suggest relevant guidance.
The assistant turns the conversation and observations into a structured service summary for the technician to review.
Before and after
Before
Searching manuals
Technicians looked through documents by hand.
After
Ask and show
Technicians ask questions out loud and add photos.
Before
Typing everything
Reports were written by hand after the job.
After
AI-drafted notes
Voice notes and observations become a structured draft.
Before
Calling senior staff
Newer technicians often escalated routine issues.
After
Guidance on the spot
The right manual sections and past fixes appear inside the job workflow.
Key features
Technicians can talk through the problem and show what they see, instead of typing everything.
Business impact
Faster work on site
The AI combines what the technician shares with manuals, service history and approved guidance.
Business impact
Better troubleshooting context
Observations, actions taken and next steps are turned into a structured report.
Business impact
Less admin after each job
Results
Faster Field Decisions
Technicians find the guidance they need with far less manual searching.
Before: Document SearchAfter: AI Assisted
Less Reporting Time
Voice notes and job details become a draft report the technician only needs to check.
Before: Manual WritingAfter: Structured Draft
Better Team Independence
More technicians can solve problems from documented knowledge before calling for help.
Before: Ask Senior StaffAfter: Contextual AI
Faster delivery
Tested components for access, AI workflow, monitoring and review cut repeated setup, so the team could focus on the company's manuals and service workflow.
Gave each technician sign-in and permissions, so the assistant only used the customer and equipment records they were cleared to see.
Handled the steps from voice and photo input to retrieving manual sections and drafting the report.
Tracked how the assistant's guidance was used on real jobs, so weak answers could be found and improved.
Sent unusual or important cases to a person before any sensitive action.
Trust and control
The assistant only reaches the information and actions approved for each technician and workflow.
Access controlledImportant or unusual cases go to a person before any sensitive action is taken.
Human reviewKey AI actions and their outcomes are recorded, so the team can see what happened on each job.
TraceableRules, prompts, workflows and controls are adjusted as the team learns how technicians use the assistant.
AdaptableTechnicians needed manuals, past service notes, customer history and troubleshooting guides while standing at the equipment. Searching documents and typing long notes on a phone took time while customers waited. Reports varied between technicians, and newer staff often had to call senior colleagues for help with routine issues.
A technician speaks to the mobile assistant and takes photos of the equipment. The AI combines those inputs with manuals, service history and approved guidance to suggest relevant next steps. At the end of the job, it turns the conversation and observations into a structured service report draft for review.
The AI only uses the information and actions approved for each user and workflow, and unusual or important cases go to a person before any sensitive action. Service reports are drafts that technicians review and approve. Key AI actions are recorded, and rules and prompts are adjusted as usage changes.
If your field teams lose time searching documents and writing reports, we can help you build an assistant they can talk to and show photos on site.