Searching part numbers across disconnected systems — before a single repair begins.
Parts failures drive repeat truck rolls — the most expensive line item you can't see coming.
Equipment telemetry exists but nobody's turning it into scheduled interventions — until it breaks.
Your best people are answering calls from the field that a knowledge system should handle.
Field service organizations spend 25–40% of engineering time on tasks that aren't service delivery — admin, documentation, knowledge search, parts translation. That overhead grows linearly with headcount. You can't hire your way out of it.
FieldPilot removes the overhead. Not by replacing engineers — by giving them intelligence at the point of work so they stop losing time to systems that were never designed for the field.
Fewer repeat dispatches. Lower cost-per-resolution.
Faster resolution. Reduced revenue impact from downtime.
AI-driven parts prediction eliminates the most avoidable cost in field ops.
Telemetry-driven predictive maintenance before failure becomes dispatch.
FieldPilot pulls diagnostic signals, service history, and real-time asset telemetry to prepare a full picture of what the engineer will encounter — before they arrive.

Searching part numbers across disconnected systems — before a single repair begins.

Engineers receive a structured brief: likely fault, confirmed parts, step-by-step resolution path — on their device before departure.

Predictive inventory models pre-stage parts at the correct location based on the day's job mix and historical failure patterns.
First-time fix improvement from pre-visit intelligence
Parts accuracy rate — trucks carry what jobs need
Reduction in dispatcher workload through automated scheduling
FieldPilot's Knowledge Agent surfaces the right resolution path in real time — drawing from service manuals, engineering notes, field history, and live diagnostics as the visit unfolds.

Step-by-step diagnostic guidance tailored to the specific asset model, fault code, and service history.

Voice-to-structured documentation. Engineers speak naturally; FieldPilot creates the service record.

If an onsite visit overruns, the dispatch agent automatically re-optimises the rest of the day's queue.
Mean time to resolution — onsite duration improvement
Repeat calls eliminated by correct first-visit resolution
Average admin time saved per visit through voice documentation
FieldPilot pulls diagnostic signals, service history, and real-time asset telemetry to prepare a full picture of what the engineer will encounter — before they arrive.

Engineer performance, SLA adherence, parts consumption, and resolution patterns — surfaced automatically to operations leadership.

Post-visit sensor data triggers proactive maintenance schedules before the next failure window opens.

Resolution steps that worked in the field get captured and surfaced automatically in future similar cases.
Productivity gain compounds as the system learns your operations
Continuous model updating — no manual retraining required
Days from deployment to measurable outcome delivery
01
Continuously monitors jobs, technician locations, skills, and SLA windows. Detects delays, reallocates resources, and notifies dispatchers before a breach occurs.
↑ Schedule compliance rate
↓ Emergency reassignment rate
↑ On-time arrival percentage
02
Validates part compatibility before dispatch, tracks van stock and depot inventory, triggers replenishment, and routes parts dynamically to technicians on the move.
100% part number lookup accuracy
↓ Emergency parts orders
↑ Right-part-first-time rate
03
Continuously monitors jobs, technician locations, skills, and SLA windows. Detects delays, reallocates resources, and notifies dispatchers before a breach occurs.
↑ First-time fix rate
↓ Mean time to repair
↓ Repeat dispatch rate
04
Unifies service manuals, OEM documentation, customer-specific procedures, ticket history, and telemetry into a single retrievable intelligence layer. Logs field activity automatically — voice-to-report, no manual re-entry.
50% faster onboarding
↓ SME dependency
↑ Documentation accuracy
↓ Compliance violations
05
Processes IoT sensor data, telemetry, and failure history to forecast equipment degradation — converting reactive emergency calls into planned interventions.
↑ Schedule compliance rate
↓ Emergency reassignment rate
↑ On-time arrival percentage
Will it survive at enterprise scale?
FieldPilot runs on ElevAIte — iOPEX's production-grade agentic AI platform. Not a proof-of-concept. Not a pilot. A system that deployed to 1,000 field engineers in 12 weeks and has run in production since, with 92% overall AI accuracy and 100% on parts lookup.
How is this different from our existing FSM tool?
ServiceNow, Salesforce FSM, SAP — they are record systems. FieldPilot layers agentic AI on top, connecting to them as data sources while adding reasoning, prediction, and autonomous action that no FSM offers out of the box.
What's the actual integration complexity?
FieldPilot connects to your existing stack through pre-built connectors for ServiceNow, Salesforce, SAP, SharePoint, and ERPs. No infrastructure overhaul. The platform ingests your data — manuals, tickets, telemetry, parts catalogs — and goes live alongside your current systems.
Will engineers actually use it?
Adoption fails when technology fights the field. FieldPilot was designed with field technicians, not just for them — voice-enabled queries, biometric login, mobile-first interface, and responses grounded in trusted documentation with source citations. Technicians stopped calling the help desk because they prefer the tool.
How does iOPEX charge for this?
Traditional providers earn revenue from truck rolls. We don't. FieldPilot is priced on outcome-linked models tied to asset uptime and SLA performance — so our incentive is the same as yours: fewer visits, faster resolution, lower cost-per-job. Cost commitments decline as the system improves.
What happens when the AI gets it wrong?
FieldPilot doesn't guess. Every response links to its source documentation. Confidence scoring runs continuously — low-confidence answers surface for SME review. Technician feedback closes the loop. The system improves with every job completed, not just at scheduled retraining cycles.
"Our technicians can retrieve this information as quickly as they can speak into the system. This is an absolute game-changer. Across a thousand-person field force — you start to form a picture of the productivity gains."
— Director, Service Innovation & Transformation, Global Retail Technology Provider

Parts number lookup accuracy
Reduction in helpdesk escalations (519 → 372/week)
Per on-site repair visit
Faster technician onboarding
Productivity gain, top users (3.5 → 4 tasks/day)
Overall AI accuracy from week one
Network uptime SLAs. High truck roll cost. Distributed field force across millions of endpoints.
POS downtime is lost revenue, every minute. Multi-vendor device complexity across hundreds of locations.
Device failure affects patient outcomes. Compliance and traceability are non-negotiable at every step.
ATM and payment infrastructure failure has regulatory and revenue implications simultaneously.
Grid and EVSE service where predictive intervention is the difference between scheduled and emergency.
Powered by ElevAIte
FieldPilot agents
RAG · Vectors · Telemetry
ServiceNow · SAP · Salesforce
RBAC · Logs · Confidence scoring
Model-agnostic. Your best LLM today — and whatever comes next.
Every response links to its source document. Technicians see the manual page, the ticket ID, the procedure number. Nothing is hallucinated.
Confidence scoring and technician feedback create a learning loop that runs in the background. The system improves with every job — no scheduled retraining, no downtime.
New product line. New customer. New OEM device. FieldPilot ingests it through standard connectors and makes it immediately available to the field.
Model monitoring, retraining, accuracy audits, SME review workflows. Your operations team never carries the AI burden — we do.