Ganymed x Encord

Enterprise-ready tools to help you deliver on your mission to delivery better orthopedic procedures. Collaborate on annotation projects, automate data annotation with AI-assisted labeling, and streamline labeling operations — securely and with best-in-class support.

Trusted by pioneering AI teams



More accurate training data for your robotic assistant, 10x faster

Super charge your data annotation with AI-powered labeling — including automated interpolation, object detection and ML-based quality control.

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Seamless collaboration with enhanced workflows

With expert QA and annotator management, create fully customized, automated ML pipelines to improve the efficiency and quality of your annotation workforce.


In-depth ontologies

Create complex ontologies

We offer the industry’s most advanced labeling ontologies enabling you to create as many nested classifications to support your labeling operations and create better Ground Truth.



Surgical Data Science Collective (SDSC)

The team were using another commercial tool and struggled with annotation quality & consistency, the quantity of video data, and the lack of a working Python SDK. With Encord, they have scaled their annotation pipelines through natively rendering videos in the Encord platform, using workflows for automating expert review, the Python SDK and more. The team are now achieving 0% incorrect annotations (previously at 20%), while speeding up video annotation by 10x.



Don’t just take our word for it


“I'm a heavy user of different data ops tools and I can confidently say that Encord is one of the best ones out there...

...Its versatility and ever-evolving nature never cease to amaze me, allowing me to annotate objects with ease and precision… The interface is simple yet powerful and making annotation-intensive studies a breeze, especially when working with multiple objects.”

- G2 reviewer


“The Encord platform is really easy to use for annotating videos...

...With Encord's interpolation feature we can label videos much more efficiently than with the tools we were using previously. The micro-model feature also makes labeling much more efficient, as we can pre-label videos so our annotators spend less time doing manual labels.”

- G2 reviewer


“The labeling automation (using object tracking and interpolation) has made it much quicker for us to label our videos....

...Combined with Encord's 'micro-models' (which further speed up video labeling) we've been able to reduce how much it costs us to create high quality labeled data. And the platform's really flexible - we're not limited by the length of the video we can upload or confined to a small range of compatible file formats."

- G2 reviewer


The leading Active Learning platform for surgical video teams

Test, validate and evaluate your models and surface, curate and prioritize the most important data for labeling, to supercharge model performance.

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Quality metrics

Boost data quality for your model

Easily uncover outliers and edge cases in your data with quality metrics.

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Semantic visual search

Custom quality metrics

Data & model debugging

Label error analysis

QA workflows

Visualize high-confidence false-positives

Use existing models and custom embeddings to surface potential label errors and correct them to improve your data quality.


Active Learning workflows

Set up automated active learning pipelines

Close the loop between your models, uncurated data and your annotation platform and target your data curation towards high-impact samples.


Encord is the leading surgical video labeling platform

We want to help you deliver on your mission to improve patient outcome, surgeon experience, and overall efficiency of joint replacement interventions.