Team CRV
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Team CRV

Powering High Stakes Data — Automating Annotations with Cord

As venture capitalists, we seek to invest in companies we believe can exponentially accelerate innovation. In my own career, I have seen several of these step changes in innovation — the democratization of mobile, the power of compute, and more recently, the rise of the developer. All three of these fundamental technology shifts gave birth to dozens of unicorns and will continue to evolve and shape the future of technology. But what really gets me excited is when a technological shift is right at the precipice — where it’s still not fully formed and may require you to still squint a bit to see the future. For me, this shift is the state of AI and data labeling. In a few short years, AI has become a critical part of enterprises across the globe. At the same time, very few of these companies have all of the tools they need to prepare quality training data — an increasingly critical component in a company’s toolkit as data becomes a long term currency for growth.

Today, there are many platforms and services that help you move your data from a provider and back in a short period of time. Those with lots of money (i.e. FAANG could also hire teams to do this in house) and avoid sending mass amounts of data externally. But when you zoom in, these services are good backups at best. They don’t take into account security threats, data privacy, or the need for specialization.

When I first met the founders of Cord, Ulrik Hansen and Eric Landau, they had a grand vision to “de-FAANG AI by making access to quality training data available beyond Silicon Valley.” They have since realized that objective with the creation of Cord. As the only company that can automate labeling using a novel algorithmic solution that makes annotation process orders of magnitude faster and cheaper, Cord eliminates the need for any outsourcing or subsequent issues crossing data across global borders.

Even better, Cord’s early customers have the highest security and quality bar. For example, Stanford Medicine’s Division of Nephrology was able to conduct experiments 5x faster after using Cord — a herculean feat. And getting labeling right in the medical AI field can be the difference between life and death — so accuracy and efficiency matters.

With a lean team and an insatiable desire to change the world — there are no better founders than Ulrik and Eric to take on this market. I can’t wait to see them build a platform that is and will continue to democratize the benefits of AI.

I am thrilled to lead the $4.5M seed with fantastic investors including YC Continuity Fund, WndrCo, and the Harvard Management Company.

The best part is — they are hiring :) https://cord.tech/careers

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Anna Khan

Anna Khan

GP @CRV, Alum @HarvardHBS @Stanford. I like a bagel with attitude.