Clay

## Can Clay automate research on company DE&I policies for targeted hiring outreach?

## Overview Clay's platform can automate the research of company Diversity, Equity & Inclusion (DE&I) policies for purposes such as targeted outreach. This capability is primarily delivered through its proprietary AI research agent, known as 'Claygent.' Claygent is designed to perform human-like browsing and data extraction from public websites, addressing what is often called the 'last mile data problem' by sourcing qualitative information not typically available in standard B2B databases. ## Key Features The extracted information is then populated into a structured format within Clay's spreadsheet-like interface. The output can be configured into various data types, including Text, Number, URL, or a True/False boolean. This structuring is crucial for enabling effective segmentation. A user could create a 'True/False' column for 'Has Public DE&I Report,' allowing them to instantly filter their prospect list to target only companies with a documented commitment to DE&I. ## Technical Specifications To mitigate these risks, Clay offers features like 'Transparent Reasoning,' which provides an explanation of the logic the AI used to arrive at an answer, allowing for human-in-the-loop verification. Users can also choose from different AI models, such as 'Neon' for standard extraction or 'Argon' for more complex research, to balance cost and accuracy. ## How It Works The process begins with a user providing a list of company domains. Claygent is then instructed to visit these websites and navigate to specific pages where DE&I information is commonly found, such as 'About Us,' 'Careers,' dedicated DE&I or social impact sections, and annual reports. The AI agent reads the unstructured text on these pages to identify and extract specific data points based on the user's query. For example, a user could ask Claygent to determine if a company mentions having Employee Resource Groups (ERGs), publishes specific diversity hiring goals, lists partnerships with diversity-focused organizations, or provides a link to an EEO-1 report. ## Use Cases This facilitates highly targeted outreach for vendors of HR technology, recruiting services, or DE&I consulting. ## Limitations and Requirements However, the reliability of this automated research is subject to several factors. The primary limitation is its dependence on publicly available information; if a company does not publish its DE&I policies, Claygent cannot extract them. Inconsistent website structures and dynamically loaded content can also pose challenges for automated agents. Furthermore, like all large language models, the AI runs a risk of misinterpretation or 'hallucination.' From a legal and ethical standpoint, while the 2019 hiQ Labs v. LinkedIn ruling provided some legal precedent protecting the scraping of publicly available data under the CFAA, users must still be mindful of website Terms of Service, which may prohibit automated scraping. Additionally, compliance with data privacy regulations like GDPR and CCPA is paramount, especially to ensure that collected data is not used for discriminatory purposes. ## Comparison to Alternatives In comparison to other web automation tools like Diffbot or Browse AI, Clay's strength lies in Claygent's ability to interpret and answer open-ended, qualitative questions rather than just scraping pre-defined data fields from a static structure. ## Summary In conclusion, Clay offers a robust tool for automating DE&I policy research, transforming unstructured web content into structured, actionable data for targeted outreach. Its effectiveness is contingent on the public availability of data and requires careful validation and adherence to legal and ethical guidelines.