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With the new funding, Labelbox will continue to invest in its platform and expand its team

Labelbox, the machine learning data platform for teams, announced today that it has raised $110 million in Series D financing. The new round was led by SoftBank Vision Fund 2, with participation from existing investors Thrive Capital, Coatue, 8VC, and Lux Capital.

The funding comes on the heels of Labelbox’s Series B and Series C rounds which closed at $53 million. With this new funding, Labelbox will continue to invest in its platform and expand its team.

Background of Labelbox

Labelbox is an enterprise-grade data labelling and AI training tool to help businesses quickly build datasets across many sectors. Founded in 2017, Labelbox saw the need for higher-quality and more efficient ways of labelling as businesses adopted machine learning initiatives and recognized the value of data labels. With a mission to unlock human potential by accelerating education and impact through technology, Labelbox demystifies ML by making it easy to build diverse datasets with the help of experts in annotation.

The software includes collaborative workflows to quickly spin up labelling projects with scalable teams of internal or external labelers, academic or expert knowledge, enforce quality control systems based on redundancy, create custom tasks suitable for specific problems and label programs with reusable templates. In addition, labels can be easily exported into most data formats for further analysis or used directly by its customers’ machine learning pipelines.

Labelbox announced its $25M Series B funding round in early 2021 led by General Catalyst which will aid its ongoing commitment to product quality and customer success initiatives. This new wave of funding enabled the company to double down on investing in artificial intelligence training platforms while expanding their team globally to accelerate innovation in ML.

Overview of the new funding

Labelbox, a leading computer vision data training platform, recently announced a new funding round of $25 million led by Index Ventures, including existing investors such as First Round Capital, Bloomberg Beta, and Gradient Ventures (Google’s AI-focused) fund), SAP.io and others. This additional funding brings Labelbox’s total capital to $43.2M. It will be used to continue investing in its platform capabilities such as the ML-assisted labelling and annotation tools for machine learning-powered data labelling tasks as well as expanding its team around the world.

The new investment will help Labelbox accelerate product innovation – from automating the entire data labelling process from start to finish with an AI-assisted data labelling user experience to making enterprise grade integrations available with Google Cloud Platform, Microsoft Azure, AWS Sagemaker and more. The Labelbox platform also provides customers with a built-in template system allowing teams to customise the label authoring process for specific use cases such as medical imaging or autonomous vehicle technology.

Funds raised in this round will also help Labelbox build transparency into its internal machine learning processes through investments in tooling around project management and collaboration between teams using different computer vision datasets. In addition, Labelbox looks to use this new capital to continue building out features that enable customers to have better control over data governance processes along with features that provide deep insights into dataset quality metrics over time so users can make more informed decisions when working with large amounts of machine learning datasets.

Impact on the Platform

Labelbox, a data platform software, has recently secured $110 million in a funding round led by SoftBank Vision Fund 2. With this new funding, Labelbox will have the opportunity to expand its platform and add to its team of employees.

This new development will mark a big step forward for the software and impact the company’s platform.

Investing in the Platform

With the new influx of investment, Labelbox is committing to further investment in its platform and expanding its team. The platform is at the core of Labelbox’s success and will remain a key focus area of development.

Labelbox will invest in improved accuracy, faster labelling speeds and comprehensive educational resources for users to quickly become experts on the system. They are also dedicated to expanding their feature set, focusing on enterprise workflows, data export options and collaboration around projects.

To make these changes happen, Labelbox is committed to extending their team size and adding additional support for existing and new product features. This commitment ensures a user experience that continues to exceed expectations and meets demands no matter what product team or industries it serves in the future.

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Expansion of the Team

Labelbox is committed to providing the best experience for its customers, which means continually investing in its platform and expanding the team who supports it. With the new funding secured, Labelbox will be able to continue to hire additional talented professionals to not only expand the current team but also bring on more specialised roles in research and engineering, product design and management, data engineering, and machine learning.

This added capacity allows Labelbox’s current engineering staff to focus more on accelerating technical solutions supporting customer success initiatives. It also extends Labelbox’s high quality customer service by providing customers an even more comprehensive discussion around training datasets, annotation techniques and validation methods. Finally, the vastness of data annotation solutions available now compared with a few years ago will provide even faster time-to-value solutions as they are brought directly onto the platform.

These investments are expected to leverage the powerful features of image labelling technologies – such as fast API integrations – which can help reduce dataset creation workflow times for data science teams so they can go from conception to market faster than ever. As products become increasingly complex and data-driven, Labelbox looks forward to transforming how organisations build successful human data intelligence projects with this new investment round.

Vision for the Future

With the new $110 million Series D led by the SoftBank Vision Fund 2, Labelbox is well-positioned to continue to invest in its platform and expand its team.

This new funding will further solidify Labelbox’s goal to ensure accuracy and security for its customers. Moreover, it will also provide the resources for them to take their platform to the next level.

Martinljubov1 (88)

Labelbox’s Goals

Labelbox’s goal is to create the world’s most effective data annotation and labelling platform. The company has identified five key areas as part of its mission to provide critical infrastructure for data-driven applications including computer vision, natural language processing, robotics, and deep learning.

Firstly, Labelbox is deepening its focus on machine learning capabilities by training their models more effectively with better data science and human annotation precision. Secondly, Labelbox will continue to invest in features that enable user collaboration and customizability within the platform. Thirdly, they are fully committed to creating a secure service designed with privacy and scalability. Fourthly, Labelbox plans on exploring new technologies that can help move data science forward such as AI/ML toolchains or cloud-native systems. Finally, they will continue expanding their global team of experts committed to advancing the industry’s leading annotation solution.

Through building a powerful combination of software engineering, data science and artificial intelligence capabilities – Labelbox aims to enable faster product development for organisations through improved collaboration on teams both near and far away from each other; significantly improving security; harnessing existing technologies; increasing flexibility with lighter-weight solutions; further diversifying industry standard practice through novel research agendas; elevating customer expectations of what can be achieved with annotation technology today; promoting global standards with worldwide technological support; increasing accuracy through greater local diversity during annotations; protecting the health & safety of personnel interacting with annotated datasets digitally – while following robust labelling protocols.

As a cornerstone commitment to its mission — Labelbox pledges 10% of its annual profits towards organisations dedicated to assisting communities affected by climate change & pollution or working at heightening opportunities for advances in research concerning global needs & wishes like healthcare/illness prevention or social justice reform (for example) — layering these efforts alongside investments into special initiatives helping further alleviate digital divides within lower income neighbourhoods throughout urban development zones (alongside rural counterparts).

Long-term Plans

Since the founding of Labelbox, we have been focused on building an excellent product that simplifies and accelerates data annotation for artificial intelligence projects. With users and customers in over 100 countries, Labelbox has established itself as an important partner in the pursuit of efficient, secure and accurate data labelling.

Now that we have received new funding, our vision for the future expands even further. We are eager to invest more in our platform to achieve better outcomes. Through expansion of team members dedicated to research and development, platform development and customer success, we can reach more people than ever before with robust labelling solutions.

Our long-term plans include continued investment into new features on our platform, such as automating data labelling processes with machine learning capabilities. By utilising natural language processing techniques tailored to model human feedback, we are confident that Labelbox will continue leading the way in solving intricate AI problems using reliable data sources for years to come. We will also explore options like cloud computing platforms so users can have access at scale from anywhere in the world without a decline in performance or accuracy.

Our commitment is even stronger now — we are focused on setting industry standards for security and trust by creating a complete system for AI developers across industries like healthcare and retail who look for smarter ways of accurately labelling large datasets faster than ever before — all while retaining privacy protections of user’s personal information.

We know sheer numbers do not measure success – a deeper connection with each customer measures it through a combination of trust earned over time through successful implementations and lasting productive relationships held between our teams. With this new funding round complete, we are well equipped with an enhanced roadmap that cements internal and external partnerships so that together we can reach newer heights within these industries where data annotation plays an important role.

Martinljubov1 (89)

Labelbox Raises $110 Million Series D Led by SoftBank Vision Fund 2

Labelbox recently raised $110 million in a Series D funding round and has seen huge success over the past few years. This funding round led by SoftBank Vision Fund 2 marks a new milestone for the company, and is a testament to the innovative products and services that LabelBox provides.

As LabelBox continues to invest in its platform and expand its team, success can be expected to continue. But, first, let’s take a look at the closing remarks.

Summary of the New Funding

Labelbox has received a significant new funding round of $36 million. This comes from a series of investors, including the venture capital firm First Round and the Silicon Valley venture firm Kleiner Perkins. The new funding will be used to grow and develop the Labelbox platform and expand staff in all areas.

Labelbox specialises in an AI development platform for training data. This means companies can develop datasets faster and accurately, allowing for more efficient product release and/or research outputs in various fields like healthcare, enterprise software, automotive, retail and more. With this new injection of capital into the system, Labelbox will be able to continue to innovate while growing their team across the board.

Labelbox is already making positive leaps on its journey, having already been named one of CB Insights’ top AI startups alongside its competitor Snorkel AI. The most recent round of funding confirms that Labelbox is on an upward trajectory, allowing them to accelerate their mission and empower companies worldwide with powerful supervised machine learning technology that delivers value quickly.

What’s Next for Labelbox

Labelbox has announced new funding of $36 million and is ready to enter its next growth phase. We are excited to accelerate the development of the platform and our team’s ability to respond quickly and accurately to customer feedback.

Labelbox is constantly exploring new ways to improve data labelling so companies across industries can better understand the data they’re collecting and use it effectively in AI-powered applications. To that end, we are introducing two new features: artificial intelligence (AI) assisted labelling, designed to help reduce manual labour, and transfer learning capabilities that enable users to drastically reduce their labelling time.

We are also expanding our team with positions in research & development, engineering, customer success, marketing, and operations so we can continue supporting the needs of our customers more efficiently. Going forward, Labelbox will focus on executing key initiatives such as platform scalability, performance optimization for enterprise users, continued investments in advanced annotation machine learning models, and meaningful collaborations with carefully selected partners to further expand our reach and strengthen our reach offering for customers.

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