Graphhopper

@graphhopper what's the driving distance and time from our Berlin office (52.5200, 13.4050) to our Munich warehouse (48.1351, 11.5820)?

Based on the route calculation, the driving distance from Berlin to Munich is approximately 584 kilometers with an estimated travel time of 5 hours 47 minutes under current traffic conditions. The route primarily follows the A9 autobahn southbound. This calculation assumes a standard car profile with typical speed limits and road conditions.

This example uses the POST Route tool for point-to-point routing. Requires an API key with routing permissions. Response times and distances vary based on selected vehicle profile (car, bike, foot) and real-time traffic data availability. Rate limits apply to batch route requests.

@graphhopper show me all areas our delivery drivers can reach within 30 minutes from our Frankfurt distribution center at 50.1109, 8.6821

The isochrone analysis reveals a 30-minute drive-time polygon covering approximately 1,200 square kilometers around Frankfurt. Key reachable areas include Offenbach, Mainz, Wiesbaden, and parts of Darmstadt. The polygon extends roughly 35km north, 28km south, 32km east, and 30km west, accounting for highway access via A3, A5, and A66. This coverage represents ideal conditions without traffic congestion.

This example demonstrates the Get Isochrone tool for service area analysis. Useful for logistics planning, delivery zone mapping, and site selection. Requires time_limit or distance_limit parameters. Polygon accuracy depends on road network data quality and does not account for real-time traffic or access restrictions.

@graphhopper we have 15 delivery stops across Hamburg today — can you optimize the route sequence to minimize total drive time for our two vans?

The vehicle routing optimization assigned 8 stops to Van 1 (total distance: 47km, duration: 2h 18m including service times) and 7 stops to Van 2 (total distance: 52km, duration: 2h 31m). The solution balanced workload across both vehicles while respecting time windows at each stop. Van 1 should start at the northern cluster near Alsterdorf, while Van 2 covers the southern route through Harburg. Total distance saved versus unoptimized routing: approximately 23km.

This example uses the GraphHopper VRP POST tool for multi-vehicle route optimization. Requires defining vehicle capacities, service time windows, and depot locations. Synchronous requests may timeout for problems with 50+ stops; consider asynchronous mode for larger fleets. API key must have VRP feature access.

When Graphhopper wins for assigning techs to service zones

A 12-person field service team needs to redraw territories after opening a new warehouse. The capacity clustering tool takes your customer list and splits them into balanced zones that minimize drive time. You run it once per quarter when headcount or depot locations change. The isochrone tool shows you the 30-minute drive radius from each tech's home base, which helps you spot coverage gaps before they become SLA misses. This works if your customer density is high enough that clustering matters—if you only have 20 stops spread across three states, you're better off eyeballing it in Google Maps. The API key setup takes five minutes and the matrix endpoint handles up to 10,000 point pairs in a single call, so you can model a full quarter's worth of stops without hitting rate limits. If you're redrawing territories more than twice a year, Graphhopper pays for itself in saved drive hours.

When the VRP tool makes sense for last-mile logistics

A 3-person e-commerce fulfillment team runs 40 deliveries per day from a single warehouse. The VRP POST tool takes your order list, vehicle constraints, and time windows, then returns optimized routes that cut daily mileage by 15-20 percent compared to manual sequencing. You call it every morning after the cutoff for same-day orders. The GPX upload tool lets you save the route and send it to drivers' phones as a trackable file. This setup works until you hit about 200 stops per day—beyond that, the synchronous VRP call starts timing out and you need a dedicated routing platform with async job queues. The geocoding tool handles address normalization so you're not manually fixing typos in customer entries. If your delivery volume is under 100 stops and you're still using spreadsheets to plan routes, Graphhopper is the fastest way to professionalize without hiring a logistics analyst.

When isochrones beat radius searches for property listings

A 5-person real estate brokerage wants to show buyers 'homes within 20 minutes of downtown' instead of the usual 5-mile radius that includes a highway dead-zone. The isochrone endpoint draws drive-time polygons that account for actual road networks and traffic patterns. You generate these once per neighborhood and cache them in your listing database. The POST route tool handles the 'show me commute time to three different offices' request that comes up in every corporate relocation. This approach works if your market has meaningful geographic barriers—if you're selling in flat-grid Midwest suburbs, a simple radius does the job. The matrix endpoint lets you precompute drive times from every listing to 50 key destinations (schools, hospitals, transit hubs) and surface them as listing metadata. If you're fielding more than 10 'how long to get to X' questions per week, Graphhopper turns that into a competitive edge.