Shav Vimalendiran

Shav Vimalendiran
Occupation	Co-Founder and CTO of SAMMY Labs
Known for	Co-founding SAMMY Labs (YC W25)
Education	Imperial College London (MEng Chemical Engineering)

Shav Vimalendiran is a software engineer and entrepreneur who is the co-founder and chief technology officer (CTO) of SAMMY Labs, an artificial intelligence company that provides an automated knowledge management platform for enterprises. SAMMY Labs was part of the Y Combinator Winter 2025 batch.

Early life and education

Vimalendiran studied at Imperial College London, where he graduated with a Master of Chemical Engineering (MEng) with First Class Honours in 2021. During his time at Imperial, he pursued coding alongside his degree, teaching himself Python and working on projects including training generative models.

Career

Prior to founding SAMMY Labs, Vimalendiran worked as a quantitative developer at an algorithmic hedge fund. He was also a founding engineer behind a multi-asset, multi-exchange cryptocurrency portfolio management and execution platform.

In October 2024, Vimalendiran co-founded SAMMY Labs alongside Joe Savidge, who serves as CEO. The company is headquartered in San Francisco. Savidge previously worked at Palantir, where he managed enterprise customer onboarding systems.

SAMMY Labs develops an AI-powered platform designed to serve as a "knowledge layer" for organisations and their AI systems. The platform focuses on automatically maintaining and updating documentation, standard operating procedures (SOPs), and compliance-related content. When regulatory or process changes occur, the system identifies affected documents and related processes, determining whether information should be updated, replaced, or enriched.

The platform integrates with existing knowledge base tools including SharePoint, Confluence, Document360, Zendesk, and Zoho. SAMMY Labs offers three core capabilities: automated maintenance of product documentation and internal SOPs using browser and desktop agents to verify processes; management of compliance, legal, and regulatory information tied to a company's products and operations; and an AI training environment that allows employees to transfer complex institutional knowledge to AI systems in a manner analogous to training a new employee.

The company positions its product as addressing what it describes as the "last mile problem" in enterprise AI — the challenge that AI systems produce unreliable outputs when the underlying documentation and knowledge bases contain outdated, contradictory, or duplicated information.