Distributed Cloud Infrastructure Startup Sync Computing Emerges from Stealth

Sync Computing, a deep tech, distributed cloud infrastructure firm, has emerged from stealth mode, unveiling its early products, client traction, and $6.1 million in investment. Sync Computing is using the computational power of physics to identify the optimal mathematical approach to offer cloud infrastructure for data, machine learning, and scientific applications.

Sync’s technology enables enterprises that operate hundreds of data pipelines per day to automatically optimize low-level computing resources, making cloud management easier, quicker, and less expensive.

Sync Computing spun out of MIT Lincoln Laboratory by Jeff Chou and Suraj Bramhavar; Activate Fellows (Cohort 2020) financed by DARPA’s Microsystems Technology Office; and MIT Startup Exchange Accelerator alumni.

Moore Strategic Ventures and National Grid Partners led the latest funding round with $6.1 million in new investments, joining existing investor The Engine. Sync Computing intends to use the additional funds to strengthen its position as a leader in modern data infrastructure and to support the further development of its accelerated data infrastructure engine and solution lines.

Large-Scale Cloud Multi-Tenant Orchestration

Photo Jeff Chou, Co-Founder and CEO at Sync Computing
“With today’s constantly expanding use of large-scale cloud computing, we’ve seen companies who have only a dozen engineers responsible for managing up to 10,000 data pipelines per day,” said Jeff Chou, Co-Founder and CEO at Sync Computing.

Sync is announcing two solutions as part of its public launch: The Sync Autotuner for Apache Spark and the Sync Orchestrator, a major step in large-scale cloud multi-tenant orchestration of complex data pipelines inspired by Sync cofounders’ PhD research on solving complex combinatorial optimization problems, which was published in Nature. The Apache Spark Sync Autotuner would minimize provisioning friction for EMR and Databricks on AWS infrastructure while substantially decreasing runtimes and job costs.

The Sync Autotuner has already been field-tested and its performance validated by a number of high-profile customers, resulting in important partnerships. With the Sync Autotuner, Duolingo, a global language learning platform with over 40 million monthly active users, slashed daily data task expenses on the cloud in half with just a minor increase in run time.

“We run many big data jobs, so optimizing our cloud processing performance is critical to our success as a business,” said Kevin Wang, analytics engineer at Duolingo. “We were impressed by Sync Computing’s delivery and appreciated their ability to predict optimized results, even before running our jobs. We are confident they can continue to help us forecast performance and reduce costs for our Spark workloads.”

Cloud Computing Expenses are Booming

In addition to active pilots with both public and private corporate clients in the SaaS, finance, and data sectors, the company recently received a $1 million contract from the U.S. Department of Defense for massive, distributed workload optimization.

The technological difficulties addressed by Sync Computing are a critical component of the exponentially expanding data infrastructure business, which Gartner estimates to be worth more than $66 billion.

Cloud costs are skyrocketing, with annual enterprise spending on cloud infrastructure services estimated to be $130 billion, according to Synergy Research, and more than 36 percent of enterprises spending more than $12 million per year on public clouds.

“Companies with data-intensive cloud workflows struggle to hire data engineers while their engineers spend unproductive time manually configuring and tuning rather than important work to move the needle on the business top line,” said Reed Sturtevant, general partner at The Engine. “We believe Sync automation can add thousands of hours of data engineering productivity every year. What Sync offers is transformative – an automatic configuration and cost-performance optimization solution for distributed cloud applications. Previously it was thought to be too mathematically complex and dynamic to solve this challenge, but Sync has figured it out.”

“With today’s constantly expanding use of large-scale cloud computing, we’ve seen companies who have only a dozen engineers responsible for managing up to 10,000 data pipelines per day – it’s physically impossible to optimize cloud infrastructure at such large scales – until now,” said Jeff Chou, Co-Founder and CEO at Sync Computing. “We’ve essentially converted large scale cloud infrastructure into a math problem, and then solve it in seconds. We are also excited to do our part in reducing the wasteful use of cloud resources and its impact on global carbon footprint. We are bullish on what 2022 will bring for us, for our customers, and for the cloud space.”