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AI Route & Day Planner

Paste your day's jobs in any format — a spreadsheet dump, a WhatsApp list, rough notes with time windows — and get a clustered, sequenced dispatch plan per crew, with a ready Google Maps route link for each.

— optional; puts your company name, logo, and local pricing on the result

How it works

1

Paste the day's jobs — spreadsheet rows, notes, any format. Mention crews and time windows.

2

The AI extracts every stop, clusters by geography, and sequences each crew's day.

3

Get arrival-time tables, conflict flags, and a Google Maps route link per crew.

You just trialed the dispatch_map + scheduler agent widget

One run here. Every job, inside Fieldproxy.

Here, you pasted a list and got one day's plan. Inside Fieldproxy, the dispatch board runs this continuously — on live drive times, all day.

  1. 1

    Jobs land with addresses already on the map — no pasting; the scheduler agent slots them as they arrive.

  2. 2

    Routes build on real road-network drive times, not estimates — and respect every window and skill constraint you've set.

  3. 3

    A tech runs long or a customer cancels — the rest of the day reshuffles itself and everyone's phone updates.

  4. 4

    Customers get live ETAs automatically; 'where's my tech' calls stop.

  5. 5

    Your dispatcher stops being a human traveling-salesman solver and starts managing exceptions.

dispatch_map + scheduler agent

See it embedded in your own workflow.

This page runs the widget once, on what you typed. The product runs it on every job, wired to your customers, price book, and techs — the result files itself and the next step kicks off automatically.

Frequently asked questions

How accurate are the drive times?

Sequences come from real geographic reasoning about your city; drive estimates are honest approximations. Each crew's Google Maps link gives you the live-traffic timing for the exact ordered route.

Can it handle constraints — time windows, equipment, crew skills?

Yes — say it in plain words ('customer only home 8-10', 'crew 1 has the mulch truck') and it pins those first, then optimizes geography around them. Anything that can't fit gets flagged, not silently dropped.

Is this the same AI as in Fieldproxy?

Same capability. Inside Fieldproxy, the dispatch board does this live on real drive-time data — jobs come in, the scheduler agent slots them, and reshuffles when a tech runs long or cancels.