UInclude offers an Inclusive Writing Tool that utilizes algorithms to identify and eliminate biased language in job descriptions, enhancing the appeal of recruitment materials. This technology increases the diversity and quality of candidate pools while reducing recruitment costs and time to hire.
Funding
$20K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many companies struggle to attract a diverse pool of qualified candidates due to unconscious bias embedded in their job descriptions and recruitment materials. This biased language can deter qualified individuals from underrepresented groups, limiting the talent pipeline and hindering diversity initiatives.
Solution
UInclude offers an Inclusive Writing Tool that leverages machine learning algorithms to identify and mitigate biased language in job descriptions and recruitment content. By scanning for subtle biases related to gender, race, age, disability, and other marginalized groups, UInclude helps organizations create more inclusive and appealing job postings. The tool provides real-time feedback and alternative suggestions, enabling recruiters and hiring managers to craft content that resonates with a broader range of candidates. UInclude's technology aims to increase applicant interest, improve the sense of belonging, and ultimately enhance the diversity and quality of the talent pipeline.
Target Audience
UInclude primarily targets recruiters, hiring managers, and HR professionals seeking to improve diversity and inclusion in their hiring processes.
Features
- Bias detection: Identifies gender, racial, disability, and age-biased language in real-time.
- Inclusive language guidance: Provides alternative word suggestions to promote inclusivity.
- Tone analysis: Detects tense or formal language to ensure job descriptions are approachable.
- Performance prediction score: Measures the overall inclusion level of job ads and predicts appeal to diverse candidates.
- Data-driven approach: Algorithms are based on scientific research, statistical analyses, and human behavioral studies.
- Comprehensive analysis: Identifies subtle language often overlooked in job ads.