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3367

Karan Brar

Logo
Karan Brar
CEO & Co-Founder of
hiloop (2026)
About

Karan Brar is Co-Founder and CEO of hiloop (YC S26), a cutting-edge AI infrastructure company building the backbone for recursive self-improvement and automated research at scale.

Before founding

Karan holds an Honours Bachelor of Science in Computer Science and Mathematics from the University of Toronto, and built deep ML expertise across roles at Dynamo AI, Reducto, and BMO Financial Group.

Founder Insights

Karan previously served as Head of ML Infrastructure at DynamoAI and as an ML engineer at Reducto, where he met his co-founder Thomas Boser and together built ML, post-training, and platform systems.

Experience

At hiloop, Karan is pioneering autoresearch infrastructure that enables AI teams to continuously improve their models and agents using their own proprietary data, running hosted or in-cloud deployments.

Scale & Impact

hiloop's platform ran 4,188 experiments in just two days using two stock coding agents and 50 B200s, beating the published state of the art on Karpathy's autoresearch benchmark and finding a NanoGPT speedrun candidate with 12.54% lower runtime than upstream.

3367

Karan Brar

hiloop
CEO
Logo
Karan Brar

Company(s)

hiloop

Industry

SaaS

Year Founded

2026

Stage/Funding

Seed

Company Location

us

Connect

About

Karan Brar is Co-Founder and CEO of hiloop (YC S26), a cutting-edge AI infrastructure company building the backbone for recursive self-improvement and automated research at scale.

Before founding

Karan holds an Honours Bachelor of Science in Computer Science and Mathematics from the University of Toronto, and built deep ML expertise across roles at Dynamo AI, Reducto, and BMO Financial Group.

Founder Insights

Karan previously served as Head of ML Infrastructure at DynamoAI and as an ML engineer at Reducto, where he met his co-founder Thomas Boser and together built ML, post-training, and platform systems.

Experience

At hiloop, Karan is pioneering autoresearch infrastructure that enables AI teams to continuously improve their models and agents using their own proprietary data, running hosted or in-cloud deployments.

Scale & Impact

hiloop's platform ran 4,188 experiments in just two days using two stock coding agents and 50 B200s, beating the published state of the art on Karpathy's autoresearch benchmark and finding a NanoGPT speedrun candidate with 12.54% lower runtime than upstream.

About

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