The use case: how Forterra deploys Encord
Forterra uses Encord to annotate multi-sensor data, including 3D LiDAR, camera, infrared and radar, as ground truth for the perception models in its autonomous ground vehicles. Its engineers work in the same interface as the annotators and connect Encord to their systems through the SDK.
More reported results
Figures published in Encord’s case study. They are not independently measured by usedby.
Faster cycles: Ground truth comes back faster and at 10x the volume, speeding up model iteration cycles by 50%.
In the customer’s words
We have more confidence that our bots can operate and complete their mission successfully. So I think you’ve seen a big difference in the performance of our systems over the last year.Other companies using Encord
Customers across industries, with public evidence.
Archetype AIConfirmed
HudlConfirmed
OnsiteIQConfirmed
Pickle RobotConfirmed
Standard AIConfirmed
Thoro.aiConfirmedGo straight to the source
Based on Encord’s published case study. We check the public evidence; the results are reported by the vendor.
encord.com- Source published
- Oct 19, 2026
- Last checked
- Oct 25, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 50%Checked
Printed word for word on the page, near the name of Forterra.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Forterra.
- The numbers in our summaryChecked
Each one is printed on the page.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Forterra uses EncordChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Faster cycles: Ground truth comes back faster and at 10x the volume, speeding up model iteration cycles by 50%.