"Labelbox serves all of our training data needs. The team is very responsive and have provided exceptional support."

“We’re pleased with how Labelbox can scale with the growth of our team or expansion of our machine learning initiatives.”

"Labelbox facilitates the collaboration and management of multiple distributed labeling workforces, and the integration between our internal processes and the Labelbox platform is easy and works like a charm."

“Field management practices and problems impacting the field vary significantly per country, field, climatic zone and field zone. Regional experts are vital to achieving high quality in annotated data.”

"Labelbox has become the foundation of our training data infrastructure. Our data science teams create high quality labeled training data with our internal domain experts as well as external labeling services, all inside Labelbox. And, the support is exceptional!"

“There are many labeling tools out there but the Labelbox backend is the real differentiator. With dynamic queueing, our labelers are never out of work, which was a major upgrade compared to our old internal tools — both from a productivity and speed-to-production point of view.”

"This is, hands down, the best part of my experience with Labelbox so far, were highly engaged, and the quality of the annotations was amazing."

“Labelbox gave us a lot of versatility by creating thoughtful ontologies with a streamlined interface. It was a critical feature and enabled us to produce high-quality labeled data with minimal errors and inconsistencies. In addition, we really liked the infinite flexibility of how classifications are set up and the product …

“What Labelbox has massively helped us with is fast iterations on our algorithms, helping us move twice as fast in this domain. The results we received from it are magnificent and their labeling user interface is the best we’ve seen for supporting our annotations efforts.”

“Labelbox has become essential to our process. It is the beginning of every single deep learning exercise we do. The only thing that comes before Labelbox is recording the data.”

“Using Labelbox was fun for my team. It became a bit of a game to see how much could be labeled and how our data affected the performance of the models. I’m very excited to see the roadmap of how Labelbox will grow. Teams of experts like mine will be …

“With the streamlined design of Labelbox, we are able to cut costs on labeling by as much as 50% while maintaining the highest quality in our training data, and get to training our models faster. With human-in-the-loop model-assisted labeling, we expect another huge reduction in time and costs to the …

“Before using the Valohai and Labelbox platforms, we struggled with managing our training data creation infrastructure and manual experiment tracking. We’re now able to concentrate on model building and deployment, without sparing engineering effort and are able to speed up model training by over 10X.”

“I found Labelbox and had a conversation with Brian. I was able to ask about the features I needed and enterprise level support.”

“Our experts found these straightforward to use and were able to annotate data very quickly to a high standard."