Encord, an AI data development platform for advanced vision and multimodal teams, announced a $30 million Series B funding round. This 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.
An AI model’s effectiveness is tied directly to the quality of the data it is built on. And as executives face increasing pressure to integrate AI into their enterprises, they often encounter the challenge of siloed, uncurated and unprepared data, significantly hindering the model development process. This issue is a major bottleneck preventing broader AI adoption. Plus, the expansion of AI highlights another critical problem: the scarcity of high-quality data and insufficient human domain experts needed to prepare this data and evaluate models for practical AI training and fine-tuning.
As opposed to depending on human supervision, Encord utilizes 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 workflow into one platform, companies have a trail showing why a model makes certain decisions. And this enables enterprises adopting AI to uncover weaknesses and easily determine the correct data that is needed to retrain the model for a better outcome. Through 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.
Encord also launched 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 like AWS S3, GCP Cloud Storage, Azure Blob and others to automate the process of curating the best data and removing uninformative or biased data. So 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.
Encord’s 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. And Encord can manage data for AI models based in images, videos, medical imagery, visual language, voice and more. With over 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, etc.
KEY QUOTES:
“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. 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.”
- Ulrik Stig Hansen, Co-Founder and President of Encord
“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.”
- Victor Riparbelli, Co-Founder and CEO of Synthesia, the billion-dollar generative AI company
“We’re seeing a lot of innovation at the model and compute layers of AI but not as much innovation at the data layer. 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.”
- J. Rylander, General Partner of Next47
