As AI agents put an ever-growing strain on traditional computer systems, Toronto-based YScope has set out to build a new way of tracking and analyzing their activity.
Allen Lau,
“This is not just a clever research project with a great demo.”
Two Small Fish
Founded in 2021 by University of Toronto (U of T) computer engineering professors and PhDs, YScope is developing open-source software for log archive storage, search, and analytics.
In a tech context, logging refers to the process of recording the events, actions, and errors that occur within computer systems. It plays a key role in compliance, troubleshooting, and security.
YScope’s Compressed Log Processor (CLP) technology aims to help organizations compress and search through vast amounts of log data without the need for decompression, reducing log management storage and compute costs. It is already being used by software engineers at companies like Meta, Uber, and Walmart.
The U of T spinout announced today that it has closed its first external financing to date, securing $3.9 million USD ($5.3 million CAD) to expand its platform, grow its 20-person team, and bring its logging infrastructure to more companies.
Raised via simple agreement for future equity (SAFE), YScope’s round was led by Toronto’s Two Small Fish Ventures, with participation from Snowflake alumni investment syndicate Snow Angels, Next Wave NYC, U of T’s UTEST accelerator, and several undisclosed entrepreneurs.
Ding Yuan is YScope’s co-founder and CEO, as well as a professor at U of T. He told BetaKit in an email that the startup aims to use the funding “to continue building CLP into the leading logging infrastructure for the AI era, where AI agents—not humans—are the primary consumers of logs.”
“These AI agents generate and analyze orders of magnitude more telemetry, creating an urgent need for a dramatically more efficient way to store, search, and understand logs,” Yuan said.
With AI agents and other intelligent systems like robots and autonomous vehicles creating a flood of new log events, Two Small Fish says it is betting that “YScope is building critical infrastructure for the next era of computing.”
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“This is not just a clever research project with a great demo,” Two Small Fish co-founder and operating partner Allen Lau wrote in a blog post. “It is infrastructure for a world that will produce exponentially more machine-generated events. As intelligence becomes cheaper and more abundant, the infrastructure required to store, search, and analyze the resulting torrent of logs becomes increasingly strategic.”
Yuan said YScope is not classifying its latest financing, noting that the startup’s tech has already proven at multiple petabyte-scale production deployments, including to power Uber’s production logging platform and manage edge log processing across more than 1.5 million connected electric vehicles.
“With a team of 20 and meaningful real-world adoption, YScope is further along than many companies raising their first outside round,” Yuan said.
With files from Madison McLauchlan.
Feature image courtesy YScope.