Explorium raises $31 million to automate data prep with AI

Explorium raises $31 million to automate data prep with AI

Venture BeatThis post was originally published by Kyle Wiggers at Venture Beat

Explorium, a Tel Aviv-based startup developing an automated data and feature discovery platform, today closed a $31 million funding round. The capital infusion comes after several banner months for Explorium, which has tripled its customer base since last September and incorporated data relevant to more industries and verticals.

Feature engineering — the process of using domain knowledge to extract features from raw data via data-mining techniques — is arduous. According to a Forbes survey, data scientists spend 80% of their time on data preparation, and 76% view it as the least enjoyable part of their work. It’s also expensive — Trifecta pegs the collective data prep cost for organizations at $450 billion.

Explorium aims to solve this by acting as a repository for a company’s information, connecting siloed internal data to thousands of external sources on the fly. Using machine learning, it claims to automatically extract, engineer, aggregate, and integrate the most relevant features from data to power sophisticated predictive algorithms, evaluating hundreds before scoring, ranking, and deploying the top performers.

Lenders and insurers can use Explorium to discover predictive variables from thousands of data sources, while retailers can tap it to forecast which customers are likely to buy each product. Within the platform, data scientists can add custom code to incorporate domain knowledge and fine-tune AI models. Additionally, they’re afforded access to tools designed to uncover optimization-informing patterns from large corpora.

In April, Explorium added a new set of signals to help organizations understand risk derived from the pandemic. By combining variables like internal company data, policy factors, and geographic factors that might affect a company’s repayment or operability, the platform generates an overall risk score. (For instance, a health system that’s considered essential and receives federal aid would have a lower risk than a hotel that’s closed and not considered critical.)

Recent Explorium clients include online small-business lender OnDeck, global media agency CrossMedia, small business banking provider BlueVine, online eyewear retailer GlassesUSA, and small business loan provider Behalf. Zeev Ventures led the series B announced this week, with participation from Dynamic Loop, Emerge, 01 Advisors, and F2 Capital. The round brings Explorium’s total funding to $50 million, which the company says will be used to expand into new business verticals and geographic markets, allowing it to grow its data catalog and hire more data science and commercial talent.

Explorium joins a raft of other startups and incumbents in the burgeoning “auto ML” segment. Databricks just last month launched a toolkit for model building and deployment, which can automate things like hyperparameter tuning, batch prediction, and model search. IBM’s Watson Studio AutoAI — which debuted in June — promises to automate enterprise AI model development, as does Microsoft’s recently enhanced Azure Machine Learning cloud service and Google’s AutoML suite.

IDC predicts that worldwide spending on cognitive and AI systems will reach $77.6 billion in 2022, up from $24 billion in revenue last year. Gartner agrees: In a recent survey of executives from thousands of businesses worldwide, it found that AI implementation grew a whopping 270% in the past four years and 37% in the past year alone.

Spread the word

This post was originally published by Kyle Wiggers at Venture Beat

Related posts