Environmental Services

Their AWS Bill Was Higher Than Their Drone Fleet

A forestry mapping company was uploading 2.7TB of drone imagery to AWS daily during fire season. The compute and egress costs hit $127K per month. Meanwhile, clients waited 2-3 days for orthomosaics that could have been done locally in 4 hours.

$127K Monthly AWS (Before)

$14K Monthly AWS (After)

4 hrs Time to Delivery

Client

North American Forestry Services Company

Industry

Environmental Services

Use Case

Drone Imagery Processing & Forest Mapping

Products Used

Expanso

Timeline

Pilot in 3 weeks, 8 field offices in 6 weeks

ROI

$1.36M annual AWS cost reduction

The Challenge

Fire season meant flying 47 drone missions per day across 8 field offices. Each mission generated 58GB of raw imagery. The workflow was simple and expensive: upload everything to S3, process in EC2, download the results. Their cellular provider loved them.

47 daily missions generating 2.7TB of raw imagery during peak season
AWS bill hit $127K per month - more than their entire drone fleet cost
Clients waited 48-72 hours for orthomosaics and change detection maps
23% of imagery failed QC after cloud processing - wasted compute
Field offices had M.2 NVMe drives sitting idle while uploading to S3
One analyst spent all day reviewing imagery quality - before processing even started

The Solution

We put GPU-equipped workstations at each field office running Expanso. Drones land, cards pop into the workstation, processing starts. Orthomosaics ready in 4 hours. AWS only sees the finished products - 58GB of raw imagery becomes 340MB of deliverables.

Field Office Processing

Each office has an RTX 4090 workstation running the full photogrammetry pipeline. Raw imagery goes from SD card to orthomosaic without leaving the building. Processing starts as drones are still landing.

Auto-QC Before Processing

ML model checks each image for blur, exposure, GPS accuracy, and overlap coverage before processing starts. Bad flight? Know in 8 minutes, not after a $200 cloud processing job.

Deliverables-Only Upload

Raw imagery stays on local NAS. Only finished orthomosaics, change detection maps, and flagged problem areas upload to AWS. 58GB becomes 340MB.

The Results

Clients now get maps the same day the drone flies. The forestry company stopped apologizing for 3-day turnarounds during fire season. AWS bill dropped from $127K to $14K monthly. The one analyst doing manual QC now does actual analysis.

89% AWS Reduction

4 hrs Delivery Time

99.4% Data Stays Local

3 weeks Pilot to Value

AWS monthly bill dropped from $127K to $14K - 89% reduction
Client delivery time improved from 48-72 hours to 4 hours
23% imagery rejection rate dropped to 4% with pre-flight QC
One analyst saved from full-time QC - now does forest health analysis
8 field offices deployed in 6 weeks after 3-week pilot
Local NAS storage cost: $0.02/GB vs S3's $0.023/GB + egress
First fire season: processed 4,127 missions without cloud delays

"Last fire season we had a client call every day asking where their maps were. This year they started asking why we're so fast. Turns out when you stop uploading 58 gigs to Virginia and back, things go quicker. Who knew."

Field Operations Manager, Forestry Services Company

Uploading imagery to process it?

If your field teams are waiting on cloud processing, we should talk. We've deployed at forestry companies, mining operations, and construction sites.

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