Mehak Aggarwal

Sybill

Sybill generates accurate and absurdly human-like summaries for sales calls and pushes them into systems where work happens - email, Slack, and CRM. 
 - Save rep time on meeting follow up by 3x
 - Give Sales Leadership signal into call outcome so they can help win a deal (+win rates)
 - Keep CRM clean with perfect call notes
 - Forecast with more accuracy due to better closing call signals
 - Manage territory churn with efficient handoffs (reduced ramp time)
 Check us out at https://www.sybill.ai/

Co-Founder (CPO and Head of AI)

Harvard University

Led AI development efforts for 3 major projects aimed at making healthcare accessible to underserved communities. First, an AI system to help radiologists diagnose cervical spine fractures in trauma victims. This technology is patented by General Electric and will undergo FDA trials for deployment on CT scanners in communities that lack trained radiologists. Second, an automated system to flag cases of intimate partner violence by correlating patient’s injury patterns with their medical history. Finally, task agnostic localisers for classification models used in medical settings. This was initially aimed at improving clinicians trust in AI systems. Used this to deploy diagnostic softwares for Covid triaging at Massachusetts General Hospital.
Further, published multiple research papers on this and other work at top AI conferences such as NIPS and MICCAI.

Research Fellow

The Hebrew University of Jerusalem

Worked with surgeons from Hadassah Israeli Hospital to develop an AI system to detect fractures. The system specialised in soft tissue fractures in forearms which otherwise have a < 30% detection rate.

Singapore University of Technology and Design (SUTD)

Developed a low-cost defense system against Spectre and Meltdown cyberattacks. Simulated out of order executions and side-channel attacks to develop mitigation patches for Visual C/C++ compilers.

Only 7% of all communication is the spoken word. Unlock your access to the remaining 93% with Sybill today. Ask me how :)

www.sybill.ai

Co-Founder (Product and AI)

Ever had that feeling when you get off a sales call, not sure what the buyer was actually interested in? What would it take to move the needle for them? Sybill understands buyer engagement and sentiment on your sales calls, so you know who the (silent) champions and detractors are, and what they specifically care about. Tailor your messaging to hit the nail on the head for each persona, and increase your win rates.
Do check this out - https://www.sybill.ai/wall-of-love
Our founding team comes from Stanford, Harvard, and UCSD, and has a deep background in machine learning and human psychology.

I never planned for this part of the story.

When I started Sybill with my cofounders, all I wanted was to build something that worked. Something people cared about enough to use twice.

There was no grand vision back then. Just an engineer turned founder trying to figure out why people said no more than yes. Trying to understand customers, rejection, and herself all at once. That journey, the messy and uncertain one, is what led me here.

I’m incredibly grateful to share that I’m starting my MBA at Stanford as a fully funded Knight-Hennessy Scholar.

As an immigrant founder, nothing about this path has been linear. From writing cold emails that never got replies, to pitching to investors from borrowed desks, to building an AI product that finally found its place, every step has been stitched together by belief and persistence.

Stanford isn’t a destination for me. It’s a reflection point to learn, unlearn, and to keep building Sybill with the same scrappy energy that started it all.

To my family, cofounders, and the Sybill team, thank you for standing with me in the grind behind the dream. And to every founder in the uncertain middle, keep going. The dots connect later, you'll see.

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