Iterative Raises $20M to Advance MLOps Platform

Iterative Secures $20 Million in Series A Funding

Iterative, a startup focused on open-source AI solutions, has announced the completion of a $20 million Series A funding round. The investment was spearheaded by 468 Capital and Florian Leibert, the co-founder of Mesosphere.

Existing investors, including True Ventures and Afore Capital, also contributed to this round, bringing the company's total raised capital to $25 million.

A Platform for Operationalizing AI Models

Iterative is developing an enterprise AI platform designed to assist companies in deploying and managing their machine learning models effectively. The platform aims to bridge the gap between model development and real-world application.

The company’s approach centers around providing data scientists and engineers with a development environment that mirrors modern GitOps practices.

The Evolution of Machine Learning Challenges

Dmitry Petrov, CEO and co-founder of Iterative, previously worked as a data scientist at Microsoft’s Bing team starting in 2013. He observes a significant shift in the industry’s focus.

Initially, the primary concern was model creation; now, the challenge lies in establishing reliable and scalable processes for machine learning, particularly within larger organizations.

“The question has evolved from ‘how do we make the person productive?’ to ‘how do we make the team productive?’” Petrov explained. “This represents a new industry-wide hurdle.”

Addressing the Needs of Smaller Companies

Petrov notes that large corporations, such as Microsoft, have the resources to develop custom tooling and processes for AI operations. However, this isn’t feasible for smaller businesses.

Iterative aims to fill this gap by offering accessible and robust solutions.

Iterative’s Core Components

Iterative’s current technology stack comprises several components that integrate with existing tools like GitLab and GitHub.

• DVC: Facilitates experiment tracking, data versioning, and model versioning.
• CML: Serves as the company’s CI/CD platform specifically tailored for machine learning workflows.
• Studio: Iterative’s newest SaaS offering, designed to enhance collaboration among teams.

The company’s strategy involves extending the collaborative capabilities data scientists already utilize with tools like GitHub and DVC to encompass data and metrics as well.

Image Credits: Iterative

“DVC Studio empowers machine learning developers to conduct numerous experiments with complete transparency,” Petrov stated. “This allows for full collaboration among developers within the organization.”

He further added that the recent funding will be used to accelerate the development and release of innovative products and services within their ecosystem.

Building an Ecosystem, Not a Monolith

Petrov emphasizes Iterative’s commitment to building an ecosystem of interconnected tools rather than a single, all-encompassing platform.

At the time of closing the funding round approximately three months ago, Iterative had a team of around 30 employees, many of whom were active contributors to the open-source projects associated with the company.

The team has since grown to nearly 60 employees.

Industry Perspective on Iterative’s Potential

Florian Leibert, general partner at 468 Capital, commented on the growing importance of data, machine learning, and AI within the broader IT landscape.

“Companies demonstrating strong open-source adoption and a bottom-up market approach, like Iterative, are poised to establish the standards for AI tools and processes related to machine learning model development,” Leibert said.