Algorithmia Raises $25M Series B to Accelerate Enterprise AI Adoption

Algorithmia’s AI Layer dramatically reduces the time and effort
required to deploy, scale and manage Machine Learning (ML) models

SEATTLE–(BUSINESS WIRE)–Algorithmia
announces it has raised $25 million in new capital, which the company
will use to expand its AI automation platform. Norwest Venture Partners
led the Series B with participation from Madrona, Gradient Ventures,
Work-Bench, Osage University Partners and Rakuten Ventures. Rama Sekhar,
a partner at Norwest, has joined Algorithmia’s board of directors.

Algorithmia, whose AI Layer platform automates DevOps for ML
applications, is targeting enterprises and government agencies that are
ready to deploy ML at scale. The AI Layer is already being used by the
United Nations, multiple US intelligence agencies, Fortune 500
companies, and over 90,000 engineers and data scientists.

“Productionizing machine learning models manually was a serious
challenge before we found Algorithmia. The AI Layer gave us the tech
stack to smoothly deploy and manage our machine learning lifecycle and
their team goes above and beyond to ensure that our efforts are
successful,” said Michael Fischer, Chief of Innovation, MS&AD a Toyota
affiliated company.

Despite the optimism around AI, adoption is being slowed by manual IT
infrastructure management tasks. An Algorithmia survey
of 500 data scientists in 2018 found that 75% of their time is spent
deploying, connecting, scaling and managing ML models manually. AI Layer
solves this problem by automating the ML DevOps lifecycle, allowing data
scientists and ML teams to collaborate and manage their portfolios of
models. Data scientists gain efficiency and can focus on building models
rather than managing infrastructure.

“Machine Learning requires a very different infrastructure and lifecycle
than traditional software,” said Diego Oppenheimer, CEO of Algorithmia.
“This investment allows us to continue to be laser-focused empowering
them to deploy and iterate their models at full speed.”

Algorithmia, which raised a $10.5 million Series A in 2017, will use the
new capital for product development, engineering talent, sales,
marketing, and international expansion. Algorithmia’s growth over the
past two years, coupled with the size of the global AI market – $4
trillion by 2022, according to Gartner – prompted the latest investment.

“AI is creating a fundamental shift in technology that is as big, if not
bigger than mobile and cloud,” said Rama Sekhar, Partner at Norwest
Venture Partners. “Every Fortune 500 CIO has an AI initiative but they
are bogged down by the difficulty of managing and deploying ML models.
Algorithmia is the clear leader in building the tools to manage the
complete machine learning lifecycle and helping customers unlock value
from their R&D investments. We’re thrilled to lead this investment and
back the incredible team at Algorithmia.”

About Algorithmia

Algorithmia is the leader in Machine Learning deployment and management.
Its AI Layer deploys and manages models in large enterprises and
government agencies worldwide. Nearly 90,000 engineers and data
scientists are deploying models on the AI Layer. For more information,
visit www.algorithmia.com.

About Norwest Venture Partners

Norwest is a premier multi-stage investment firm managing more than $7.5
billion in capital. Since inception, Norwest has funded 600+ companies
and currently partners with more than 140 active companies across its
venture and growth equity portfolio. The firm invests in early to late
stage businesses across a wide range of sectors with a focus on
consumer, enterprise, and healthcare. The Norwest team offers a deep
network of connections, operating experience, and a wide range of
impactful services to help CEOs and founders scale their businesses. The
firm has offices in Palo Alto and San Francisco, with subsidiaries in
India and Israel. For more information, please visit www.nvp.com.
Follow Norwest on Twitter @NorwestVP.

Contacts

Kevin Wolf
TGPR
(650) 483-1552
kevin@tgprllc.com

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