Aarav Bajaj is Co-Founder at Aegis, an AI-powered platform automating insurance denial appeals for healthcare providers. The company participated in Y Combinator's X25 Spring 2025 batch and helps providers recover revenue lost to denied claims.

Aarav graduated from Carnegie Mellon University with a degree in Computer Science and Machine Learning. He previously worked as a Software Engineer at Palantir Technologies, where he deployed data-driven solutions at scale, and built an enterprise AI platform for Parsons Corporation, a $7B+ public company.

Aarav co-authored AI research and was a National Merit Scholarship Winner, selected from a pool of 16,000 finalists. The idea for Aegis came when his own anesthesia claim was denied, inspiring him to solve the broken healthcare appeals system.

Aegis cuts the cost of appealing a denial by 80% and reduces filing time from 2+ hours to under 2 minutes. The platform raised $500K from investors including Y Combinator, Rebel Fund, and The Impact Venture.

Aegis addresses a $260B+ annual problem where US healthcare providers lose money to denied claims, yet fewer than 15% of denials are appealed even though over 50% of appeals succeed. The platform integrates with major EHRs and insurance companies to automate the entire appeals process end-to-end.