Toronto-based Shakudo has secured $9.5 million CAD ($7.2 million USD) in Series A funding to help companies launch artificial intelligence (AI) products more quickly and cost-effectively.
As AI hype abounds and companies scramble to invest in and deploy AI technologies, Shakudo says it aims to help firms take advantage of the slew of new data and AI tools available to them, without locking them into a single vendor or set of offerings.
“What we do is we make it easy for companies to start using these technologies.”
– Yevgeniy Vahlis, Shakudo
In an exclusive interview with BetaKit, Shakudo co-founder and CEO Yevgeniy Vahlis said the startup plans to use the capital to “expand heavily” into enterprise generative AI, where Shakudo has seen strong demand from both new and existing customers.
“It felt like the right time to seize the opportunity in the market,” he added.
Founded in 2021 by AI experts from Georgian Partners, Borealis AI, and BMO, Shakudo aims to make it easier for firms to adopt AI through its software platform. The startup’s end-to-end offering enables enterprise data science and machine learning (ML) teams to design, develop, test, and roll out AI products.
“We don’t build foundational models like many of the other new entrants into the market,” Vahlis said. “What we do is we make it easy for companies to start using these technologies.”
Shakudo’s all-equity Series A round, which closed in April, was led by San Francisco-based GreatPoint Ventures with support from fellow new investor, England’s RTP Global. Toronto-based Golden Ventures and California’s Parade Ventures, which co-led Shakudo’s $4.2-million seed round in 2021, also participated in the firm’s most recent round, which brings Shakudo’s total funding to about $14.5 million. Vahlis declined to disclose Shakudo’s latest valuation, but claimed it was a “substantial up round” relative to its seed financing.
According to GreatPoint general partner DJ Patil, today, “numerous challenges hinder effective AI implementation,” from complex data infrastructure needs, to compatibility issues with the latest tools, and talent scarcity.
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“This is where Shakudo plays a vital role,” Patil told BetaKit. “With its unified platform for building and managing enterprise-grade data stacks, Shakudo provides a seamless solution to overcome these obstacles.”
Patil, who is joining Shakudo’s board as part of the round, knows data science well—an early member of LinkedIn’s senior leadership team, he also helped coin the term “data scientist,” and served as the White House’s first United States chief data scientist.
To date, Shakudo has helped companies like Quantum Metric, QuadReal, RiskThinking, Ritual, EnPowered, and ZeroEyes launch a wide variety of different products. Clients have used Shakudo’s platform to deploy large language models (LLMs), summarize analyst research, structure unstructured text, detect weapons in security camera feeds, classify waste using computer vision, generate digital twins of physical assets, and forecast energy usage.
Shakudo, which describes itself as “the operating system for data stacks,” claims its platform automates many common engineering and development tasks, freeing up clients’ engineers to focus on building products. As many tech companies shed staff and preserve cash amid the downturn, Vahlis believes that this value proposition has become particularly appealing.
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“Taking away the mundane maintenance and operational aspects of the data stack is even more valuable to them than ever before,” argued Vahlis. “No one has redundant people on their team right now.”
In a difficult fundraising environment, Vahlis claimed that Shakudo’s “lean” 12-person team, strong revenue growth, and customer retention helped the company stand out. The CEO claimed Shakudo grew its revenue 6x year-over-year in 2022 with no sales team, but declined to disclose exact figures.
For his part, Patil acknowledged that these results played a role in the firm’s decision to invest in Shakudo and lead its latest round. “Shakudo’s strong performance and ability to thrive in adverse conditions gave us confidence in their potential for long-term success,” Patil said.
“Shakudo had the right product, at the right time, with a great team, and the numbers to back it up.”
As Golden Ventures partner Jamie Rosenblatt told BetaKit, “Shakudo had the right product, at the right time, with a great team, and the numbers to back it up.”
From a market-timing standpoint, Rosenblatt claimed that enterprise interest in AI adoption “has never been more intense.”
“Post-OpenAI, everyone is trying to figure out how to integrate an LLM into their stack,” he said, noting that this presents a “massive opportunity” for Shakudo from a customer-acquisition perspective.
As it looks to tackle this opportunity and bring more large enterprises to its platform, Shakudo plans to double its headcount by adding engineering and go-to-market talent.
Feature image courtesy Shakudo.
