a Nexage AI agent
Field service and maintenance agent

Diagnoses the fault,
sends the right technician.

A sensor alarm or a customer call; the agent classifies the fault, derives the probable cause from past interventions, matches the part and skill needed and suggests the best technician with the route. Step-by-step procedure and device history for the technician, SLA and warranty checks for the service manager. Work order assignment and out-of-warranty charging decisions always rest with service management.

Fault classification and probable causePart and skill matchingTechnician and route suggestionSLA and warranty checks
Saha Servis Ajanı karakteri
Field Service Agent
Field Service Agenttask flow · on-premise
Sample task flow · every approval is written to corporate memory
!probable cause: fan failure · 78%
✓technician 40 min · part in stock
First visittarget increase in first-visit fix rate · right part, right skill · sample
Minutesfrom alarm to work order suggestion · sample
SLAand warranty are checked automatically on every work order
Servicemanagement approval is required before any work order is assigned or charged

It takes over diagnosis and planning; the service team focuses on the field

The agent learns fault records, device history, part stock and technician skills; suggests the right match to reduce second visits, tracks SLA and warranty, and brings the service manager only the work that needs a decision.

Fault classification and probable cause

Classifies the customer call or IoT alarm by fault type; ranks probable causes by likelihood from past interventions on the same device family and prepares a checklist for the technician.

"Compressor temperature alarm → fan motor 78%, dirty condenser 14%"

Spare part and skill matching

Searches the warehouse and van stock for the part the probable cause needs; determines the competence required (certificate, device training). If the part is missing, suggests an alternative with the supply time.

"Fan motor FM-220: 3 in Izmir warehouse · refrigeration certificate required"

Best technician and route

Suggests a technician by skill, distance, current workload and SLA time; reorganizes the day's route and informs the customer of the estimated arrival. The assignment decision rests with the service manager.

"Technician Mehmet · 40 min · after today's 2nd job"

Procedure and intervention history for the technician

Brings the device's 23 past interventions, the step-by-step check procedure, diagram and safety notes to the technician's mobile screen; answers questions asked in the field from the manual.

"Step 4/9: fan relay check · last replaced 14 months ago"

SLA and warranty checks

Checks the SLA time in the customer contract and the device's warranty status on every work order; warns about SLA breach risk in advance and prepares a charging suggestion for out-of-warranty work.

"SLA 8 hours · 5 h 20 min left · under warranty"

Service report and second-visit risk

Drafts the service report from the technician's field notes and the replaced part; flags recurring fault patterns and second-visit risk and makes suggestions to maintenance planning.

"Report draft ready · second-visit risk: low"

A sample day with the field service agent

A representative working day: from the sensor alarm to the service report, which work the agent prepares alone and which it submits for the service manager's approval. Every intervention outcome is taught to the next similar fault.

  1. Sensor: compressor temperature alarm
    Cooling unit SU-1187 in Izmir reported above-threshold temperature. The agent opens the device record, the contract and the 23 past interventions.
  2. Probable cause: fan motor failure (78%)
    A similar alarm pattern in the same device family was closed 11 times with a fan motor. Second possibility a dirty condenser (14%). A checklist is prepared for the technician.
  3. Part in stock, technician 40 minutes away
    Fan motor FM-220: 3 in the Izmir warehouse. Of the 2 refrigeration-certified technicians, Mehmet is 40 minutes away, free after his second job. SLA 8 hours, under warranty.
  4. Service manager approved the work order
    The manager reviewed the suggestion and assigned Mehmet; instruction to the warehouse to load the part into the van. The customer was told an estimated arrival of 11:30.
  5. Technician on site: procedure and history on screen
    In the mobile app: the 9-step check procedure, wiring diagram and the last fan replacement (14 months ago). At step 4 the fan relay was found faulty; motor and relay replaced.
  6. Service report draft ready
    Report from the field notes and replaced parts; under warranty, no charge. Second-visit risk low; condenser cleaning added as a suggestion for the next periodic maintenance.
  7. Daily summary to the service manager
    14 work orders: 11 closed on the first visit, 2 waiting for parts, 1 SLA risk prioritized for tomorrow morning. 3 recurring-fault suggestions to maintenance planning.
Field Service Agent
Fault diagnosis and dispatch card · sampleIoT alarm + device history · 1 suggestion, awaiting approval

A compressor temperature alarm arrives from a cooling unit; the agent classifies the fault, derives the probable cause from 23 past interventions, matches part stock and the nearest suitable technician, checks SLA and warranty and presents a work order suggestion to the service manager.

fault_2026-09-14_SU-1187.jsonCooling unit SU-1187 · Izmir
Fault typeKompresör sıcaklık alarmıclassified
Probable causeFan motoru %78 · kondenser %14from history
PartFM-220 · İzmir depo: 3 adetin stock
TechnicianMehmet · 40 dk · soğutma sertifikalıawaiting approval
SLA / warranty8 saat · kapsam içichecked
Probable cause: fan motor failure (78%)Warranty: covered · SLA 8 hoursSend work order for approval

How does it work in your company?

Pick your industry to see which work the field service agent takes over and how it works with your team.

Field Service Agent — Manufacturing sector
Sample tasklive
Customer: AC not cooling, outdoor unit making noise, 2 years old.
Model X-12, under warranty (3 years). 64% of similar complaints were closed with a fan motor, 22% with a gas leak. The fan motor is in the Kadıköy van; technician Ayşe is free tomorrow 10:00–12:00. If you approve the appointment, an SMS goes to the customer.

Hundreds of calls a day; a second visit with the wrong part is the most expensive mistake.

Turns the complaint in the call-centre record into a fault type, derives the probable cause from the model and history, matches the part with van stock; organizes regional technicians' daily routes, clarifies warranty and extra charge status during the call.

  • Fault type from the callTurns phrases like "not cooling, making noise" into a model-based fault type.
  • Van stock matchingChecks whether the needed part is in the technician's van; loading list if not.
  • Daily routeOrders regional technicians' appointments by distance and SLA.
  • Warranty and charge informationStates the warranty status during the call, submits the out-of-warranty charge estimate for approval.
Call→ fault type
Vanstock matching
Warrantyclear on the call

Four steps, in-house

  1. 01

    Connect

    IoT/SCADA, service management, ERP (stock, warranty, contracts), map/routing and the technician mobile app are connected; device records, service procedures and past intervention records are uploaded.

  2. 02

    Teach

    Rules are defined with the service team: fault classes, technician skill matrix, SLA and warranty rules, which work orders are suggested automatically and which go to the manager for approval.

  3. 03

    Run

    The agent classifies alarms and calls, derives the probable cause and part, suggests a technician and route; work order assignment and out-of-warranty charging are always finalized with service management approval.

  4. 04

    Improve

    Every intervention outcome (actual cause, replaced part, duration) is written to corporate memory; the probable-cause estimate sharpens with every closed work order, and recurring faults are reported to maintenance planning.

Systems it connects to
IoT / SCADAService management (FSM)ERP (stock, warranty, contracts)Maps and routingTechnician mobile appCall centre and CRM

The agent works; decisions stay with the company

Every agent runs on-premise or in your own cloud; what it may do alone and what it submits for approval is defined by the authority matrix.

Runs in-house

Device, customer and sensor data never leave the company; the agent runs on-premise or in your own cloud. Customer contract and location data are protected under KVKK rules.

Authority matrix

What the agent does alone and what it submits for approval: defined by work order type, amount and role. Technician assignment and out-of-warranty charging always rest with service management.

Source and trail for every diagnosis

Which past interventions the probable cause rests on, which data produced the part and technician suggestion: the agent shows it. Every alarm, work order and decision is recorded with a timestamp.

Human in the loop

A diagnosis is a probability; the final call is the technician's on site and the assignment is the service manager's. The agent ranks, matches and reminds; it never skips a safety step.

Common questions

Does it work without IoT or sensor data?

Yes. The agent starts from the call-centre record, e-mail or a technician report; it classifies the fault from the customer's description and the device history. When IoT/SCADA is connected the same flow is triggered by the alarm; both sources also work together.

Which mobile app do technicians use?

If you have an existing service management app it integrates with it; otherwise the mobile screen of the Nexage Service & Field module is used. The technician sees the work order, procedure, device history and route on the phone and enters field notes and photos on the same screen.

How are warranty and SLA rules defined?

Customer contracts and warranty conditions (period, coverage, exclusions) are defined as rules together with the service team and matched with the warranty record in the ERP. The agent checks them on every work order; unclear cases go to service management for a decision.

How reliable is the probable-cause estimate?

The estimate is produced as a likelihood from past interventions on the same device family and the source records are shown; it gives the technician a checklist, not a verdict. The final diagnosis belongs to the technician on site; every closed work order sharpens the estimate.

Does the agent assign technicians by itself?

No. It suggests by skill, distance, workload and SLA; the assignment stays with the service manager or dispatcher. On emergency calls the suggestion is prioritized and presented instantly, and approval is one click.

Where is device and customer data stored?

Data stays on-premise or in your own cloud; nothing is transferred outside. Customer location and contract data is opened only to the relevant roles by the authority matrix, and every access is logged.

How long does setup take and how is it priced?

Usually 4–8 weeks including system connections, device records and rule definition; it varies with the scope of IoT integration. Pricing is an annual license + setup based on the number of technicians, monthly work order volume and connected systems; a firm quote follows discovery.

See the field service agent with your own fault records

In a 30-minute demo we run a few real fault records from last month together; see with your own eyes how the agent derives the probable cause, matches the technician and part, and what it leaves to the service manager.

İzmir R&D Center: Dokuz Eylül University Main Campus, Doğuş Caddesi No:207/Z DEPARK Alfa Building, BambuGO, Buca / İzmir
Istanbul Office: Maya Anatolium Tower, Floor 3, Kollektif House, Nexage Yazılım, No: 307, 34880 Kartal / Istanbul
E-mail and phone: info@nexage.ai · 0 549 763 21 88