Jordan is HieCOR's Field Operations AI. Every morning before your dispatch team walks in, Jordan has already read every unassigned job, every technician's current workload and skill set, every open parts position, and every customer's time window — and prepared a ranked, optimized dispatch plan. Your dispatcher confirms. The day starts on time.
What Jordan Does
Jordan manages the operational complexity of running a field service team — from morning queue prioritization through real-time exception management.
Jordan ranks every unassigned job by urgency — SLA commitments, warranty deadlines, rescheduled customers, commercial accounts, and promised dates.
Jordan evaluates each job against every technician — proximity, skill set, parts on-hand, and workload — and recommends the best-fit assignment. Dispatcher confirms in one click.
Jordan sequences each technician's stops by location, job duration, and customer time window — then flags any sequence with inefficient travel, timing conflict, or window risk.
Jordan monitors every active job — flagging jobs running over expected duration, approaching a promised window, or in a zone conflict — with lead time for the dispatcher to act.
Jordan triggers automated texts at every milestone — appointment confirmation, arrival window, en-route, and completion — without manual action.
Jordan tracks completion rate, average job duration vs estimate, drive time vs job time, first-visit fix rate, and technician utilization.
Jordan in Action
The route board shows every technician's active stop, completed stops, and remaining schedule in real time. Jordan built this plan before the morning briefing — reading 34 unassigned jobs, 8 technicians, parts availability, and customer time windows simultaneously. Every sequence is optimized. Every conflict is already resolved.
A Day With Jordan
Jordan works from before the day begins through the last completion confirmation.
Overnight job queue review
Jordan reads 28 unassigned jobs and 9 technicians' current workloads. By 7:00am Jordan has a complete recommended dispatch plan with assignment, routing, and customer notification schedule for every job.
Dispatcher arrives to a plan — not a blank board.
Parts shortage at dispatch
Jordan checks parts requirements. Two technicians are short a required part. Jordan surfaces the nearest warehouse location and calculates which tech can stop to pick it up without pushing their first customer outside the window.
Both problems resolved before either technician leaves the shop.
Job running over schedule
A HVAC repair estimated at 90 minutes is now at 2 hours with no completion update. Jordan flags the overrun and prepares an arrival window update for the next customer.
Dispatcher sends the updated window. Customer informed 40 minutes before their window expires.
Emergency commercial call
A priority commercial account calls in an emergency HVAC failure. Jordan identifies the nearest technician with HVAC certification and a 90-minute gap in their schedule.
Dispatcher picks the top recommendation and re-routes in under 2 minutes.
Day-close exception review
Jordan surfaces 4 items for tomorrow's queue: 1 job prioritized from today, 1 job awaiting a part restock, and 2 jobs where completion notes suggest a return visit is likely.
Tomorrow's queue is already prioritized before the dispatcher logs off.
Where Jordan Works
Jordan connects to every operational workflow that affects field service performance.
Scheduling & Dispatch
Jordan is the AI engine behind the dispatch board — providing recommendations, monitoring the active schedule, and flagging exceptions.
Explore Scheduling & Dispatch →Routing & Scheduling
Jordan builds and optimizes daily routes — sequencing stops, balancing time windows, and re-optimizing dynamically.
Explore Routing & Scheduling →Parts Inventory
Jordan checks parts availability before every dispatch decision and identifies the nearest resolution for shortages.
Explore Parts Inventory →2-Way Text Messaging
Jordan triggers automated customer notifications at every milestone from the dispatch and route records.
Explore 2-Way Text Messaging →Work Orders
Jordan reviews work order exceptions and feeds that data into the next day's dispatch priorities.
Explore Work Orders →Reporting & Analytics
Jordan's daily route data feeds the field operations reporting dashboard.
Explore Reporting & Analytics →FAQ
How does Jordan recommend technician assignments?
Jordan evaluates each job against every available technician — comparing proximity, skill set, parts on the truck, and current workload — and surfaces the best-fit recommendation. The dispatcher confirms with one click.
Does Jordan optimize routes automatically?
Jordan sequences each technician's stops by location, job duration, and customer time window — and flags any sequence with inefficient travel, timing conflicts, or arrival window risks. When a job moves, Jordan re-optimizes automatically.
How does Jordan handle emergency calls mid-route?
Jordan identifies available technicians ranked by proximity, skill set, and available time. The dispatcher picks the top recommendation and re-routes in minutes. The affected customer is notified automatically.
What does Jordan flag in real time during the day?
Jordan monitors every active job and flags jobs running over expected duration, approaching a promised window, and zone or routing conflicts — with enough lead time for the dispatcher to act.
How does Jordan send automated customer notifications?
Jordan triggers automated texts at every service and delivery milestone — appointment confirmation, arrival window, en-route notification, and completion confirmation. All from the job record, no manual action.
Does Jordan check parts before dispatch?
Yes. Jordan checks parts required for each job against the assigned technician's truck inventory and the nearest warehouse. Shortages are surfaced with resolution options.
Most businesses who go through a HieCOR demo immediately see where Jordan would change their daily workflow — and how many tasks currently falling through the cracks would get handled automatically.
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No commitment required · US-based implementation team · Average onboarding: 45 days