Logistics & Supply ChainAI Agents & Automations28 Weeks
Multi-stop trip planning in Austin required users to coordinate across three to four separate apps for every outing. We built an AI agent that consolidates search, routing, and scheduling into one conversation that delivers an optimized plan in seconds.
Under 30 Seconds
Route Generation Time
9 in 10 Routes
First-Suggestion Acceptance
Under 1 Quarter
Development Cost Payback
“We had a clear picture of what the app needed to do and the end result nailed it. Users get a full optimized route in about 30 seconds.”
Mike Scott
Client Lead, Pitstop Navigator
Before
15 to 20 minutes across multiple apps, Route and search handled separately, Manual stop sequencing for each trip
After
30 second AI optimized routes, One conversational agent for everything, Automatic sequencing by drive time
Narrative
The Challenge
Planning a multi-stop trip typically took 15 to 20 minutes because no single tool combined business search with live route awareness. Users had to coordinate across separate apps, and the results they got back never accounted for where they were actually driving. That gap meant extra miles, missed stops, and a planning process that took longer than the errands themselves.
What We Built
We built an AI agent on top of a geospatial database loaded with thousands of local business listings, all indexed by proximity to any given route. Users tell the agent what they need in plain language, the system finds qualifying businesses near the path and sequences them so each stop adds as little drive time as possible. From first message to a fully mapped route, the whole thing wraps up in under 30 seconds.
Results
15 to 20 minutes of trip planning dropped to under 30 seconds. Three to four apps got replaced by a single conversation. Nine out of ten routes were accepted on the first try without any manual edits. Premium subscriptions hit recurring revenue in the first quarter and covered the entire build cost earlier than projected.
Story gallery
Technical proof
Implementation details and the stack behind the delivery.
Implementation highlights
Key engineering decisions from this project.
Stack snapshot
Tools and platforms used in the delivery.
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