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Curious Context Labs

Operations · Agent

Scheduling and dispatch

AI scheduling and dispatch for field service teams

Proposes the day's job schedule from skills, locations and parts, then updates crews and customers when plans change.

01 today

The problem

The dispatcher builds tomorrow's schedule in their head and on a whiteboard, juggling who has the right skills, who is nearest and which van has the parts. One sick day or overrunning job means an hour of phone calls. Customers get vague time windows and ring in to ask where their technician is.

02 the run

What the AI does

  1. Step 1: Reads open jobs, crew skills, availability and van stock from ServiceTitan, Jobber or Housecall Pro.
  2. Step 2: Builds a proposed schedule that groups jobs by area and matches each one to a qualified person, using Google Maps travel times.
  3. Step 3: Explains each assignment in plain words, such as nearest qualified technician or only crew with the part on board.
  4. Step 4: Re-plans the rest of the day when a job overruns, a cancellation comes in or someone calls in sick.
  5. Step 5: Texts customers through Twilio with their arrival window and sends updates when it changes.

paused: waiting for a person to approve

03 human in the loop

Where a person approves

The dispatcher reviews and approves the proposed schedule each day, and confirms any mid-day change before crews or customers are told.

04 after

What changes

The dispatcher starts from a sensible draft instead of a blank board, and changes during the day take minutes rather than a string of calls. Customers know when to expect someone.

Results from a real build

[CASE STUDY] We only publish results we can name and check with the client.

see also

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Tell us how your business runs. We'll tell you where AI fits.

A free 30-minute call. You talk, we ask questions, and you leave with a few concrete ideas — or an honest answer that AI isn't the right fix yet.

Working with teams in the United States, United Kingdom and Australia.