Workflow automation startup Parabola raises $24M in funding to help automate manual work without coding

Parabola, a San Francisco-based startup that helps everyone automate their manual tasks without coding, announced today it has secured $24 million in Series B funding to hire more staff and bolster its research and development (R&D) efforts.

The round, which brings the company’s total funding to $34.2 million, including the latest tranche, was led by OpenView, with participation from investors including Flexport alongside Matrix, Thrive Capital, Good Friends, Webflow, Otherwise Fund, Abstract Ventures, and Merus Capital.

The news comes almost three years after the startup raised $8 million in Series A funding led by Matrix Partners, with backing from Thrive Capital, Elad Gil, and additional angels as well as the company’s previous investors. In conjunction with the funding, Parabola also announced new partners including Flexport, who Yaseen described as one of the company’s favorite customers.

Parabola was founded in 2017 by CEO Alex Yaseen and Mike Lang, both of whom brought unique expertise to the table. Alex Yaseen, a former strategy and operations consultant at Deloitte, possessed extensive experience in performing comprehensive data analysis and constructing models for data analysis and process optimization. On the other hand, Mike Lang, a software engineer at Yahoo! Sports, was responsible for building the RESTful web service layer for one of Yahoo’s most popular APIs.

Drawing from their diverse backgrounds, Yaseen and Lang embarked on a mission to create a product that combined the best practices of software engineering with the evolving and sophisticated data requirements of knowledge workers. Their goal was to develop a solution that empowered individuals across various roles, including sales, marketing, product management, and more, to become self-sufficient in their data-related tasks, without the need for an engineering background. The result of their collaboration is a powerful product that enables users to leverage data effectively and be self-reliant in achieving their goals.

In a blog post, Parabola founder and CEO Alex Yaseen said, “This new investment reinforces the notion that 2023 is the year of the operator. Raising funds in this environment is tough, especially a Series B, but it’s the companies that bring true, tangible ROI that will succeed — and we believe Parabola can and will do so. We can’t wait to show you the new features we’re working on.”

You may be wondering what exactly Parabola does. In essence, Parabola is a platform that leverages artificial intelligence (AI) to automate a wide range of workflows. With Parabola, customers can streamline their processes by utilizing its capabilities to handle different types of documents such as PDFs, text message logs, images, and emails. The platform enables users to perform tasks like standardizing, enriching, and categorizing these documents, providing them with a more efficient and consistent workflow automation solution.

Parabola was founded with the goal of empowering individuals without technical backgrounds to harness the power of data and automate processes without the need for coding skills. The platform offers a user-friendly drag-and-drop interface, eliminating the need for tedious manual work. This intuitive interface allows users to streamline their workflows, freeing up valuable time and energy to concentrate on their unique areas of expertise. With Parabola, users can overcome technical barriers and focus on maximizing their productivity and specialization.

Here’s how Yaseen describes the company: “Our core differentiator is our ability to be owned directly by an operations team to build solutions to their own problems without getting bottlenecked on data and IT.” He added, “This enables them to automate workflows that otherwise are too fast-changing for engineers to write code on their behalf.”

“Many users choose to stick with their outdated and mundane processes because it’s what they’re familiar with, and they believe that their complex datasets cannot be automated,” he added. “[But] enterprise leaders can no longer exhaust valuable engineering resources on projects that can be achieved otherwise … We’ve built a suite of collaboration features that turn the ‘individual use-case’ into a ‘company use-case,’ allowing operations teams to align on best practices and ultimately build off one another’s work.”