The Unit Testing Toolkit for

Computer Vision

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

Trusted by pioneering AI teams

Auto-find label errors

Find label errors in your training data automatically, with no more manual inspection. Use vector embeddings, AI-assisted quality metrics, and model predictions to find problematic data samples and course correct.

Learn more about label errors
Auto-find label errors

Instantly search your data with natural language search

A brand new way to search your visual data, Active empowers you to search and curate your data using only natural language. Search across your images, videos, DICOM files, labels, metadata, and more using Active’s natural language search.

Learn more about Natural Language Search

Debug models and boost performance

Find and fix dataset errors, biases, and edge cases. Conduct model error analysis and run automated robustness tests to uncover failure modes and issues, while delivering results in explainability reports to your team.

Learn more about data validation

Understand what impacts your model performance

Use out-of-the-box metrics or integrate your own to get detailed breakdowns of how your data and labels affect your models. Version and compare your datasets and models to track your progress.

Learn more about model evaluation

Surface, curate, and 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 find failure models and curate high-value data to boost model performance.

Learn more about automated data inspection

Your ML pipeline, your way

Connect your secure cloud storage, MLOps tools, and wider stack with dedicated integrations that slot seamlessly into your workflows.

annotate icon

Maintain regulatory compliance

Stay on top of ever-increasing compliance and regulation with total visibility into every step of the model production process.

Learn more about AI compliance and security
bg gradient

Build better models, faster with Encord

The future of AI starts today. Encord’s advanced developer tools and infrastructure securely empower AI teams to streamline data flows, collaborate with ease, and build reliable models in one platform.

Built with security in mind

Encord is SOC2, HIPAA, and GDPR compliant with robust security and encryption standards.

Pre-built integrations

Import data from your desired storage bucket such as AWS, Azure, Google Cloud Storage and Open Telekom Cloud OSS.

Encord API & SDK

Programatically access projects, datasets and labels within the platform via API.

"Encord Active ticks all of our boxes and helps us achieve results we thought were 1-2 years away...

...We have a lot of models in production and wanted a tool that could help our team 1) understand why a model was not working for a particular use case and 2) quickly tag some of this data and send it back to our team to improve. We use Encord Active to explore and tag data, find label errors, and find areas where the model is failing - but mostly to improve our model performance while speeding up this loop for us, so our team doesn't need to diagnose issues blindly and is also freed from a lot of the lower-value manual work that slowed us down."

"It's seriously impressive. By far the most fleshed out continuous learning system I have seen...

...We were using [a big data annotation platform] before we found Encord Active. How it worked is you had to put in your own metrics and each data point (as metadata), and then it would show you some failure modes and errors based on what you put in. But Encord Active is all automatic computation — it's much more informative in deciphering that metadata, and it surfaced insights we had never found through that previous platform and that we would also never be able to deduce from manual analysis."

"We improved overall last-mile performance by 2% and edge-case class by 67%...

...We started with implementing the recommendations for 1 of 6 low-performing classes we got based on Encord Active insights into our synthetic data generation pipeline. With this, we improved the per-class performance from 0% to 67% (AP50) and 0% to 100% (P1). The next steps are to implement changes for all low-performing classes in our dataset based on our insights."

One Active Learning Platform To 
Turn Your Data Into AI

Forget fragmented workflows, annotation tools, and Notebooks for building computer vision models. Encord is an active learning platform that accelerates every stage of taking a computer vision model to production.