Founded as Recognai in 2017 by now-CEO Daniel Vila Suero and CTO Francisco Aranda, the company rebranded in October 2022 to become Argilla, which comes from the Latin term for “clay.”
“We’re moving away from ‘data is the new oil’ to ‘data is the new clay,’” Vila Suero explained in a blog post announcing the change. “We shape models by providing high-quality inputs to our models (be it prompts, training examples, or user feedback).”
Like other branches of machine learning, NLP tech is only as good as its training data, but traditional data annotation (i.e., hand-labeling thousands of training examples) can be expensive and time-consuming.
As the Chief Growth Officer of AI data training company LXT pointed out in a recent SlatorPod, the language data labeling space has become much more competitive with more than 150 companies now serving the fast-growing market.
Open-Sourced with a Chance of Cloud
Argilla’s platform — open-sourced in 2021 — is intended to help data and ML teams efficiently build and monitor high-quality training data.
Data teams can use the platform to collaborate with domain experts, quickly refining content to form high-quality training data, and then tailor pre-trained models to specific use cases.
According to Argilla, the company’s platform is already used by “dozens of companies in healthcare, IT, media, financial services, and other sectors,” along with “thousands of users and community members from America, Europe, Africa, and Asia.”
Slator 2022 Language Industry M&A and Funding Report
44-pages on 2022 translation and localization industry acquisitions and translation startup investments, with valuations, deal rationale.
Argilla has also opened up registration for early access to the forthcoming Argilla Cloud, an online workspace that does not require users to host and maintain the platform locally. The cloud offering is expected to be available globally sometime in Q1 2023.
While Argilla has not publicly specified how it plans to use the new funding, its six-person team is currently looking to expand to include two engineers — specialized in NLP and Python, respectively — and a product manager.