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Encord Secures $30M in Series B Funding and Introduces Encord Index to Automate AI Data Curation and Management

• Led by Next47, the Series B financing includes participation from existing investors Y Combinator, CRV, and Crane Venture Partners doubling down.

• Encord’s new Index feature enables teams to efficiently manage and curate large datasets to train, fine-tune and deploy high-performing models faster.


SAN FRANCISCO, CA – WEBWIRE

Encord, the AI data development platform for advanced vision and multimodal teams, today announces a $30M Series B fundraise. The round was led by Next47, a global venture firm investing in early and expansion-stage companies in SaaS, AI and enterprise, with participation from existing investors Y Combinator, CRV, and Crane Venture Partners.

The effectiveness of an AI model is tied directly to the quality of the data it is built on. As executives face increasing pressure to integrate AI into their enterprises, they often encounter the challenge of siloed, uncurated and unprepared data, which significantly hampers the model development process. This issue is a major bottleneck preventing broader AI adoption. Moreover, the expansion of AI highlights another critical problem: the scarcity of well curated high-quality data and the insufficient number of human domain experts needed to prepare this data and evaluate models for effective AI training and fine-tuning.

As opposed to solely relying on human supervision, Encord leverages automation to give AI teams everything they need to make large datasets AI-ready and get models to production faster. Encord’s software addresses all four steps of turning data into AI: data management, curation, annotation and model evaluation. By consolidating this entire workflow into one platform, companies have a trail that shows why a model is making certain decisions. This allows enterprises adopting AI to uncover weaknesses and easily determine the correct data that is needed to retrain the model for a better outcome. With a software-first approach, Encord easily scales with customers as their data volume and model output increases, addressing the limitations of other tools and purely human supervision.

“In 10 years, every company will have an AI department in the same way that they have an IT department today or risk losing relevance, and Encord will be the only platform they need to accomplish the process of turning data into functional AI models,” said Ulrik Stig Hansen, Co-Founder and President of Encord. “As AI models begin tackling increasingly complex problems, the access to and management of data will only become more crucial. By leading with automation, we’ve built a scalable solution to support customers on every step of their AI journey.”

To bring even more ease to the management and curation steps of the process, Encord is also launching Encord Index, an end-to-end data management tool that allows customers to visualize, search, sort, and control their internal data that will be used to train and create AI models. Index integrates seamlessly with data storage such as AWS S3, GCP Cloud Storage, Azure Blob and others to automate the process of curating the best data and removing uninformative or biased data. As a result, Encord customers have achieved a 35% reduction in dataset size by curating the best data, see upwards of 20% improvement in model performance and save hundreds of thousands of dollars in compute and human annotation costs.

“Successful state of the art models, like our recently released Expressive Avatar foundation model EXPRESS-1, require highly sophisticated infrastructure. Encord Index is a high-performance system for our AI data, enabling us to sort and search at any level of complexity. This supports our continuous efforts to push the boundaries of AI avatar technology and meet customer needs” said Victor Riparbelli, Co-Founder and CEO of Synthesia, the billion-dollar generative AI company.

The Encord platform was built on the foundation of vision, an inherently more complex modality than text, positioning the company to lead the imminent multimodal era, outpacing those who are currently solely focused on LLMs with the current hype cycle. Encord can manage data for AI models based in images, videos, medical imagery, visual language, voice and more. With more than 2,000 predictive and generative models put into production, Encord is trusted by over 120 of the top AI teams from organizations such as Synthesia, Philips, Zoopla, Cedars-Sinai, Northwell Health, and many more.

“We’re seeing a lot of innovation at the model and compute layers of AI but not as much innovation at the data layer,” said T.J. Rylander, General Partner of Next47. “Encord’s forward-thinking platform addresses one of the biggest challenges in AI today – understanding and managing the data that will give enterprises high quality, reliable outcomes from their AI applications, therefore lowering the risk of AI implementation. The market has long needed a solution for the AI data problem and we are proud to back Encord as the startup that has found it.”

For more information about Encord, please visit https://encord.com/.

About Encord

Built by a team of former quants, physicists, and computer scientists, Encord is a leading data development platform built to make AI development more practical. Encord’s end-to-end solution is the first unified platform that automates an AI team’s entire workflow (data management and curation, model evaluation, and annotation). By combining data curation and annotation with an evaluation of model quality, customers have access to a trail that shows why a model is making certain decisions.



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 Encord Ai
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 Y Combinator


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