Yotascale builds a platform to track, attribute and manage cloud spend so engineering teams can understand costs across services and avoid misattribution. Its product today focuses on AWS and the company plans to add Azure and Google Cloud support. Yotascale targets heads of platform engineering and emphasizes earning engineers' trust to prevent cost data from being used against infrastructure teams. Founder and CEO Asim Razzaq began working on Yotascale in mid 2015, initially self‑funding before taking outside capital. The company reported 4x year‑over‑year ARR growth this year, though the CEO declined to share specific revenue figures. Yotascale has scaled cautiously—hiring a chief revenue officer in 2018—and prioritizes measured fundraising and product‑market fit over large, rapid raises. YotaScale provides an AI-powered Autonomous Cloud Operations platform that delivers intelligent, actionable insights to cloud operations teams. The system uses proprietary machine learning algorithms to process millions of data signals, providing contextually relevant, real-time anomaly detection and recommendations that can be acted upon immediately. The platform enables teams to take application needs into account and optimize infrastructure to meet business needs. YotaScale announced general availability of its platform and has been deployed by enterprise customers including AdRoll, Highfive, HomeAway, ProtectWise and Reltio. Led by CEO and co-founder Asim Razzaq, the company raised $8m in a Series A financing, bringing total funding to $11.6m. Investors include Crosslink Capital (lead), Pelion Venture Partners and Engineering Capital; prior backers and angels participated in an earlier round in 2017. YotaScale is a graduate of Alchemist’s enterprise accelerator that builds a machine-learning platform to automate cloud performance management for enterprises. The company combines usage, billing and log data to detect anomalies, make forward projections and contextualize fluctuations against expected performance. Its technology uses ensemble machine-learning techniques, with regression models as a foundation and semi-supervised models for specific uses. YotaScale focuses on balancing performance, availability and cost across heterogeneous cloud infrastructure and time intervals. Customers mentioned in the article include Apigee and Zenefits. Competitors in the space include CloudHealth Technologies and Cloudability.

Total raised

$25M

Funding rounds

3

Latest round

Series B

Latest activity

Oct 2020