Deepset Secures $30 Million in Funding to Enhance Its Large Language Model-Focused Machine Learning Operations Solutions

Deepset, a platform for building enterprise apps powered by large language models (LLMs) akin to ChatGPT, has announced that it raised $30 million in a funding round led by Balderton Capital with participation from GV and Harpoon Ventures. The proceeds will be put toward expanding Deepset’s products and services and growing its team from around 50 people to 70 to 75 by the end of the year, co-founder and CEO Milos Rusic says.

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Industry Shifts Towards AI Factories

Rusic notes that the industry is shifting from AI labs to AI factories. "It’s not anymore about tinkering around, it’s about shipping successful products and value," he said in an email interview with TechCrunch. This shift is driven by the growing demands of product teams and end-users in the enterprise.

Data Science Teams Overworked and Overburdened

According to a recent poll, data engineers are experiencing burnout, likely to leave their current company for another within 12 months and considering quitting the industry altogether. This state of affairs is contributing to challenges around AI development within the enterprise. A 2022 Gartner poll found that only around half of AI projects make the leap from pilot to production, and 53% of machine learning models are never deployed.

Deepset’s Ambitions Outgrow Haystack

Rusic co-launched Deepset with Malte Pietsch and Timo Möller in 2018, bootstrapping the business by building a platform called Haystack. However, as the company grew, its ambitions outgrew Haystack. "It was an incredible foundation for us to build on, but we quickly realized that we needed something more robust," Rusic said.

Deepset Cloud

To address this need, Deepset built Deepset Cloud, a platform that allows customers to use various LLMs simultaneously, combining them in the application architecture to avoid vendor lock-in and mitigating data privacy and model sovereignty issues. "It’s often 10x faster to repeatedly build production-ready NLP and LLM services with Deepset Cloud as opposed to hiring, training and managing a dedicated team for robust back-end application development," Rusic said.

Customer Pipelines

Deepset has hundreds of customer pipelines running on its platform, including workloads for Siemens and Airbus. Legal publishing house Manz tapped Deepset to launch an internal AI-powered tool that helps to surface court documents, related precedents, and more. Airbus is using Haystack to build apps that recommend aircraft operations guidelines to pilots in the cockpit.

Topics

AI: Large language models (LLMs) are changing the way companies develop their products and services.
Enterprise: Deepset’s platform is designed for enterprise customers who need to use LLMs in their applications.
Funding: The $30 million funding round will be used to expand Deepset’s products and services and grow its team.
MLops: Deepset’s platform is part of the broader MLops (Machine Learning Operations) space, which focuses on the development and deployment of machine learning models.

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