Sample case studies

We work with some of the world's leading AI companies, enterprises, hospitals, and research institutions.

Stanford Medicine
Stanford Medicine

The Division of Nephrology reduced experiment duration by 80% while processing 3x more images.

Problem
Stanford was using three different pieces of software to identify, annotate, and count podocytes and glomeruli in microscopy images.
Solution
Stanford started using Encord's annotation tools & SDK to automate segmentations, count, and calculate sizes of segments.
Results
With Encord, Stanford researchers reduced experiment duration from an average of 21 to 4 days while processing 3x the number of images.
80%
Reduction in experiment duration
3X
Number of images
1 platform
... and not 3
Undraw surveillance
Top-3 human behaviour surveillance AI company

The company built custom label structures with Encord's adaptive ontology & automated workflows with Encord's SDK.

Problem
Complex annotation tasks rendered existing & open-source tools unusable. GDPR & privacy restrictions prohibited use of managed service.
Solution
Utilised Encord to build custom pose estimation templates, integrate to their cloud for compliance, operate tracking modules to automate annotations.
Results
Built a highly sophisticated human behaviour dataset. Automation features made in-house workforce practical.
GDPR & Privacy
Compliant
Custom label structures
Flexible ontology
97%
Automated labels
KCL Logo
King's College London

KCL used Encord to achieve a 6.4x average increase in labeling efficiency for GI videos.

Problem
Using clinicians to annotate pre-cancerous polyp videos had prohibitively high costs to produce large datasets.
Solution
Deployed Encord's micro-model module to increase clinician labeling efficiency and automate 97% of produced labels.
Results
Highest expense clinician saw 16x labeling efficiency improvement. Cut model development time from 1 year to 2 months.
6.4X
Faster than manual labeling
97%
Automated labels
6X
Faster to AI in production
KCL Logo
Leading restaurant automation provider

The automation provider tracked objects across different views & replaced 37 annotation hours with 1.

Problem
Tracking objects across different views coupled with changing weather & lighting conditions led to annotation inconsistencies & high costs.
Solution
Deployed Encord's micro-model & interpolation modules to track objects across different views, enforce consistency, & increase labeling efficiency.
Results
37x increase in labeling efficiency. Annotation accuracy increased from 94% to 99%.
37X
Faster than manual labeling
4pp
Accuracy boost
99%
Annotation accuracy
MSK logo
Memorial Sloan Kettering Cancer Center

MSK adopted Encord to build custom label protocols for pulmonary thrombosis projects.

Problem
Detecting and classifying vena cava filters in complex label protocols (ontologies) rendered existing & open-source tools unusable.
Solution
Deployed Encord's label protocol studio to build custom protocols, DICOM annotation tool, worklists & automation modules to increase efficiency.
Results
Project made feasible by the flexibility offered by Encord's ontology study.
1000+
Protocol configurations
10 minutes
Total setup time
100%
Auditable

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