About Snorkel AI
Snorkel AI develops a system for programmatically building and managing training datasets. The company's platform allows users to develop training datasets and reduces the time, cost, and friction of labeling training data. It was founded in 2015 and is based in Redwood City, California.
Snorkel AI's Product Videos
ESPs containing Snorkel AI
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
The machine learning training data curation market offers solutions to support data quality control in the AI algorithm training process. These solutions help organizations complete key tasks, such as selecting the best subsets of data for training models, triaging datasets for bias, and identifying labeling errors. Ultimately, these solutions help minimize the downstream effects of poor-quality…
Snorkel AI's Products & Differentiators
Snorkel Flow provides a data-centric AI platform for AI/ML teams to: Label training data programmatically and accelerate AI development 10-100x Use model error analysis from continuously updated models to guide data/AI development Adapt to real-world changes with a few clicks rather than complete relabeling
Research containing Snorkel AI
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned Snorkel AI in 8 CB Insights research briefs, most recently on Oct 13, 2023.
Expert Collections containing Snorkel AI
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
Snorkel AI is included in 4 Expert Collections, including Unicorns- Billion Dollar Startups.
Unicorns- Billion Dollar Startups
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Companies working on generative AI applications and infrastructure.
Latest Snorkel AI News
Nov 9, 2023
During the data labeling step, usually, a team of humans will identify data points, whether that’s the severity of the damage in 100,000 photos of different cars for an insurance company, or the sentiments of people who interact with support agents for a customer service company. Data annotation is a critical step in the training of large-language models (LLMs) like OpenAI’s GPT because it makes AI models more accurate. Advertisement Following OpenAI’s release of ChatGPT last November, data annotation companies have received so much demand that it is pushing some of them to raise prices. Advertisement Realeyes is a company based in London that uses computer vision to read and understand human behavior; that data is then used to improve advertising effectiveness or to minimize identity fraud. Since the company was collecting and labeling data for its own computer vision algorithms, the company decided two years ago to move into an analogous service of data labeling for other companies, said Mihkel Jäätma, the CEO of Realeyes, which works with over 200 companies across media, technology, and advertising. Advertisement The data labeling service began generating revenue last year, with the business getting “very big, very quickly,” he said. Jäätma estimates that 80% of the business comes from companies essentially looking to make avatars less cartoonish. “It’s really kind of exploded to be a very substantial part of our business only in the last two years and keeps going that way,” he said. From the likes of big tech companies and well-funded AI startups, “[t]he investment that we see is that this is going to be overlaid with very human-like [features],” he said. In other words, the work now is to make these avatars—bots that exhibit personalities based on made-up characters or real people—understand users and talk in a more human way. Advertisement Since the launch of its data labeling service, Realeyes has raised prices at least twice. Jäätma said he has had to tell customers that if they weren’t willing to pay up, Realeyes would not complete the full request. Making avatars more human-like Labeling audio and visual recording is complex. It’s not just data scrapped from the Internet. Human annotators work on assessing people’s emotions, for example—and as that work gets more nuanced, it means paying the annotators more. (Realeyes was reportedly hired by Meta to make the tech giant’s avatars, which rolled out its own AI avatars in September , more human.) Advertisement Meanwhile, Snorkel AI, a company specializing in data labeling, said that the number of inquiries it received in the past three months was more than five times the total number received in the entire previous year, with requests coming from early-stage startups building large-language models (LLMs), as well as government agencies and IT companies. The Redwood City, California-based company has not raised prices, but it has rolled out additional service offerings around AI training since customers’ needs have diversified. Advertisement Data labeling is already a $2.2 billion industry The growth in data labeling shows that generative AI applications are making progress. “With ChatGPT and other developments, the applications of AI are not out of reach,” said Devang Sachdev, vice president of marketing at Snorkel AI. The surge in AI products comes as LLMs from the likes of Google and OpenAI have also become much more accessible. Advertisement The global data collection and labeling market hit $2.2 billion in 2022 and it is expected to grow nearly 30% from 2023 to 2030, according to market research firm Grand View Research. 📬 Sign up for the Daily Brief Our free, fast, and fun briefing on the global economy, delivered every weekday morning.
Snorkel AI Frequently Asked Questions (FAQ)
When was Snorkel AI founded?
Snorkel AI was founded in 2015.
Where is Snorkel AI's headquarters?
Snorkel AI's headquarters is located at 55 Perry Street, Redwood City.
What is Snorkel AI's latest funding round?
Snorkel AI's latest funding round is Series C.
How much did Snorkel AI raise?
Snorkel AI raised a total of $135M.
Who are the investors of Snorkel AI?
Investors of Snorkel AI include Greylock Partners, Google Ventures, Lightspeed Venture Partners, Nepenthe Capital, BlackRock and 8 more.
Who are Snorkel AI's competitors?
Competitors of Snorkel AI include Cleanlab, CrowdWorks, Datasaur, Superb AI, Encord and 7 more.
What products does Snorkel AI offer?
Snorkel AI's products include Snorke Flow.
Who are Snorkel AI's customers?
Customers of Snorkel AI include Chubb, BNY Mellon, F500 Telecom, F500 Biotech and Top 3 US Bank.
Compare Snorkel AI to Competitors
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Sama provides training data for artificial intelligence (AI) and machine learning (ML) algorithms. It focuses on video, image, language, and sensor data annotations and validation. The company provides its service to a wide range of industries such as media, technology, retail, agriculture, and transportation. It was formerly known as Samasource. The company was founded in 2008 and is based in San Francisco, California.
Datasaur develops smart tools to help make natural language processing (NLP) labeling productive. It offers a platform that collaborate and its built-in intelligence catches errors by flagging inconsistent labels. The company was founded in 2019 and is based in Livermore, California.
AIMMO provides a data analysis and smart automation platform. It offers a solution for the acquisition, curation, labeling, and augmentation of structured data. It serves fields including autonomous vehicles, smart cities, industry 4.0, robotics, and security sectors. AIMMO was founded in 2016 and is based in Seongnam, South Korea.