Datasaur vs. Label Studio

There are a few reasons why you may have found this post:

1. You are shopping around and exploring to see if there is a data labeling platform that meets your requirements.
   
   
2. You’re looking for a platform that can host not only you but a team of project managers, reviewers, and annotators.
   
   
3. You have found that spreadsheets are not able to efficiently solve your data labeling requirements and you know you need software that can help. Internal tools will take months to build and years to maintain.
   
   
4. You are a data scientist, ML/NLP engineer, or linguist who is focused on building better training data for your team.

Deciding which data labeling platform to use is a crucial decision for each organization. A quick Google search will surface a range of different companies promising a premiere labeling product. Text, audio, video, and image labeling are the most prominent forms of data annotation available, and every company specializes in one or two—though most will offer every option. Subsequently, deciding on the best labeling platform for your team can feel overwhelming. You need to make sure that their labeling platform matches their teams’ current requirements and roadmap for the years ahead.

In this post, we will talk through the feature differences between Datasaur and Label Studio. These two organizations have made a prominent impact in the market. So, without further ado, let's begin!

TL;DR: What is the Distinction Between Datasaur and Label Studio?

The following is a brief summation of the differences between Label Studio and Datasaur: 

1. Datasaur is a labeling platform that specializes in NLP. Within the first three years of the company’s growth, Datasaur has created audio, text, and OCR feature functions. Label Studio provides the ability to label audio, photos, text, HTML, and time series. 
2. Datasaur hosts an advanced workforce management tooling system. The Datasaur UI contains dashboards and tables that provide insights into team and individual members’ production and quality of labeling. Label Studio does not offer reporting on labeler progress within a project. However, the organization does offer reporting and analytics on team production for enterprise customers.     
3. Both Datasaur and Label Studio list three different price ranges: Free, Growth (Label Studio calls it “Teams”), and Enterprise. Neither company offers a team space for the free version. For the middle tier, Label Studio offers less features than they do for their Enterprise. All of the product features Datasaur hosts are offered to both Growth and Enterprise customers, the main difference for us is the number of people using the platform. 
4. Both Datasaur and Label Studio offer a review interface to resolve conflicts and sustain quality control. However, Datasaur goes one step further and offers a review interface to all customers. 

Brief History and Mission of Both Companies

Label Studio was founded as an open source tool. It boasts an active community of contributors on its Github and Slack. The labeling platform is now owned by Heartex. Because of the open source nature of the tool, any user can download the platform for free. As previously mentioned, though, some features will not be included in their free version.

When describing what brought them to develop Label Studio, Nikolai Liubimov stated the emphasis of their platform is on simplicity. They aim for Label Studio to be quickly configurable for many data types. Nikolai also writes that machine learning configuration is a core tenet of what makes Label Studio so effective.

As mentioned in the TL;DR: section, Label Studio offers text, audio, image, and video labeling. They have been a trusted platform by prominent companies such as Facebook, IBM, Intel, and more.

Here is an example of the image-labeling experience in Label Studio. The labeling is quick and efficient. As shown in this example, choosing a label and drawing the corresponding bounding box can be done in a few short seconds.

Label Studio also enables the user to annotate using time series classifications. Platform support for such workflows is rare, which speaks to Label Studio’s creativity and commitment in supporting niche requirements and use cases. 

Datasaur was founded in 2019. Ivan Lee, the founder, spent hundreds of millions of dollars solving NLP labeling needs at Apple and Yahoo. During his tenure at these companies, Ivan discovered NLP labeling was a massive hole in the AI industry. He founded Datasaur with the intent of specializing in NLP, for text and audio use cases. 

Datasaur began in the winter of 2019 with a small team of five. With Ivan’s product management experience, the company began to grow immediately. After graduating from YCombinator, Datasaur took investment from Initialized Capital and the CTOs of OpenAI and Segment. Within the first few years, Datasaur earned prominent customers such as Zoom, Spotify, Netflix, and many more. These customers choose Datasaur for their premiere NLP labeling for text and audio.

From the very beginning, Datasaur has grown and collaborated with its customers; the core philosophy of Datasaur is to evolve with the needs of customers. After only three years, Datasaur now has over 50 employees working together to build a product that grows as our customers do.

While many annotation tools have started with Computer Vision, Datasaur saw that NLP was an underperforming area of the AI industry. Which is why Datasaur is committed to creating the most comprehensive and innovative NLP labeling tool. The Datasaur mission is to host a comprehensive suite that caters to all NLP needs.

How NLP Labeling Tasks Thrive on Datasaur

Both Datasaur and Label Studio provide a platform to annotate audio and text datasets. However, Datasaur’s platform is designed to maximize efficiency and simplicity. The power user can customize for their needs and efficiently label in Datasaur. Our users span from labeling specialists to data scientists to new contractors who need to use a platform that is as simple as a spreadsheet. In this way, Datasaur has made itself a plug-and-play solution for any type of user. 

Experience Labeling with Complete Efficiency and Simplicity

In this section, we will cover all of the ways in which Datasaur provides simplicity and customizability.

Simple, easy-to-learn interface

Non-technical users can thrive within Datasaur’s interface. The first observation you may have is that the labelset being applied to the data is visually prominent (see below). Furthermore, each label has a corresponding hotkey so the labeler can keep their hands on their keyboard during the entire annotation experience. Finally, the labeler can draw relationships between labels by merely double clicking on a label and connecting it to another. All of these features are intuitive and efficiently available. 

(Datasaur places the labels above the tokens, not obstructing the reading view)

(Label Studio places the label after the word it has been applied to)

Both Datasaur and Label Studio enable text classification and token based labeling such as NER. Audio is also offered by both companies.

However, they approach audio labeling very differently. Datasaur enables the user to label the transcript of the audio file. They can also create timestamps that correspond to their label in the transcription.

Label Studio allows the user to classify the audio file within the audio. They can create timestamps in the audio and then classify such items like emotion or sentiment analysis. Furthermore, a user can create a transcription for the audio within the interface.

(In this example, the labeler is classifying emotion within the audio file)

In Datasaur, you can upload a transcript alongside your audio file. The user can also create the transcription within the labeling interface. In the same interface, the annotator can then label the transcription and create corresponding timestamps in the audio wave file.

Who holds the advantage in audio is determined by the user’s requirements. Label Studio enables classifying the audio itself. Datasaur enables labeling the transcription and creating corresponding timestamps for those labels. Datasaur’s audio functionality provides more, but such granularity may be unnecessary for your use-case.

(In this example from Datasaur, we see the user creating a timestamp and then linking it to a label in the transcription.) 

Label Studio offers more annotation options: photo, video, audio, time series, and text. Datasaur offers more in-depth feature functions within text and audio. Furthermore, Datasaur is only focused on further developing text and audio capabilities. Subsequently, Datasaur is the more premiere service within NLP specifically, while Label Studio is a generalized platform.

Label Studio is the best option if your requirements contain photo, video, or time series.

If you only have NLP requirements, Datasaur is the best platform hands down. 

Three Reasons Companies Choose Datasaur

1. An Easy, Intuitive Labeling Interface for Labelers, Reviewers, and Managers

Datasaur is a perfect solution for many NLP requirements. NER, POS, and Coreference are just some of the NLP workflows a team can deploy on Datasaur. We’ve also had teams deploy labelsets with more than 15,000 labels while being able to maintain a simple and easy interface to navigate. A user in consumer electronics said this about Datasaur: 

2. An Easy to Use Platform with Excellent Customer Service

Datasaur is never too far from you, as the team is spread across the globe. This enables the organization to respond to every message quickly. Every message is answered within a few hours, at the most. Not only that, Datasaur offers personal support. This means that when you reach out to us, you'll connect with a real human who knows the ins and outs of your data labeling needs.

The support that Datasaur provides does not end at customer service. It extends to a very involved onboarding process. Datasaur launches a three-month onboarding journey for every new customer. This journey includes a host of meetings to ensure each customer is comfortable with deploying their requirements on Datasaur and connecting with the team to make sure the product meets their needs.

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3. Datasaur is Secure‍

Datasaur secures your data; the company is SOC 2 Type II compliant and HIPAA compliant. Safety and iron-clad security are top priorities for Datasaur.

So, is Datasaur for you?

Datasaur is for you if:

• You need a simple, production ready NLP labeling solution
• You are looking for a platform that offers a complete workforce management tool
• You require a SOC 2/HIPAA compliant solution that can deploy to VPC/on-premise

Datasaur is NOT for you if:

• You are annotating data that is not text or audio
• You want the platform to also provide first-party annotation services

We hope you find the platform that is best suited to your needs. If you have NLP labeling needs, request a demo today to see how Datasaur could streamline your data labeling.