Cevian Labs provides AI-powered tools that automate academic CV analysis and faculty decision-making processes. Their flagship product, CVParsa, extracts and contextualizes information from academic CVs, while COI Pond converts CVs into draft NSF Collaborators and Other Affiliations forms. The platform helps faculty and administrators reduce manual work and generate accurate insights in minutes.
Funding
Funding not disclosed
Founders
Product
Problem
Faculty and administrators spend significant time manually reviewing CVs and preparing documents like grant-related affiliation forms, which is error-prone and detracts from core academic work. This inefficiency slows down decision-making processes such as hiring, promotion, and grant submissions, creating bottlenecks that burden university staff.
Solution
Cevian Labs provides a secure, cloud-based platform that automates the extraction and contextualization of academic CV data using machine learning. The platform's flagship model, CVParsa, parses CVs to capture contact details, education, employment, scholarly interests, mentoring, funding, awards, teaching, and service history. A second tool, COI Pond, converts existing CVs into draft NSF Collaborators and Other Affiliations forms, allowing users to edit and download the result. By reducing manual effort, the platform delivers accurate, structured insights in minutes so faculty and administrators can focus on higher-value intellectual work.
Target Audience
Primary users are university faculty and administrators who need faster, data-driven insights for academic review processes, including grant preparation, hiring, and promotion workflows.
Features
- CVParsa machine learning model automatically extracts structured data from academic CVs, including contact details, education, employment, scholarly interests, mentoring, funding, awards, teaching, and service
- COI Pond tool automatically identifies advisors, advisees, collaborators, coauthors, and editors from a CV to generate a draft NSF Collaborators and Other Affiliations form
- Online editing interface for draft COA forms with export to xlsx format for direct upload with grant proposals
- Secure platform designed to reduce human error in manual academic document review
- Scalable infrastructure supporting efficient academic decision-making across multiple institutional workflows