Outlier Detection with Encord Active
Easily uncover outliers and edge cases in your data and labels with Encord Active’s quality metrics. Boost data quality and supercharge your model’s performance.
Trusted by pioneering AI teams
Encord Active
Data-driven insights to power model performance
Identify and address data that deviates significantly from the rest of your dataset based on pre-defined or custom metrics.
active learning pipelines
Surface, curate, & prioritize the most valuable data
Not all data impacts your model equally. Build active learning pipelines by combining acquisition functions with your data distribution, model confidence, and similarity search to detect outliers and curate high-value data to boost model performance.
Learn more about automated data inspection
NLP search
Instantly search your data with natural language search
Harness the power of natural language to seamlessly search and curate your images, videos, DICOM files, labels, and metadata. Intuitive data exploration for outlier detection.
Learn more about natural language search
find & fix errors
Auto-find & fix label issues
Automatically detect label issues in your training data . Use vector embeddings, AI-assisted quality metrics, and model predictions to detect errors or outliers and course correct.
Learn more about outlier detection
OUR CUSTOMERS
Don’t just take our word for it
Whether you've just started collecting data, labeled your first batch of samples, or have multiple models in production, Encord Active can help you.
“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.
- Victor, G2 reviewer
“I really like how the software makes it easy to label videos...
...The interpolation feature is really helpful and makes it way faster than the other tools I've used before. Also, the micro-model feature is really cool because it lets me pre-label videos so it's less work for me.”
- Jessie, 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.”
- Conrad, G2 reviewer
“One of the best bits of Encord are the powerful ontologies we can create...
...We can build a really complex labelling structure to cover advanced labelling requirements. Even more useful when combined with the action classification - means you can create very rich datasets to train a ML model on.”
- G2 reviewer
“For research and the other things, I am a heavy user of different annotation 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
“This was the first tool we found that could handle the enormous labeling taxonomy we had.....
...We have to catalog many different types of products and Encord’s ontology feature was extremely useful in packing everything into a usable structure. The interface is also quite intuitive and the hotkeys make it easy for our team to navigate and speed up the annotation process.”
- Victor, G2 reviewer
case study
Why they chose Encord
Problem
Certain classes of data underperforming and needed to analyze the source of the discrepanciesSolution
Encord Active’s quality metrics and model failure modes
Improved overall last-mile by 2%
Improved edge-cases by 67%
“Diving deep into the performance on a class-by-class basis allowed us to tackle some of the worst-performing classes and improve their performance based on insights from analysis of the datasets”
Try Encord today
