The year in review
As we reach the end of 2022 I’d like to take the time to reflect on what has been a momentous 12 months for Seldon and the ML and AI world. It is fantastic to mark the end of the year with a whole range of new product releases, notably Seldon Deploy Advanced and our OSS Core V2, all which are a huge step forward towards the data-centric MLOps platform of the future.
A dramatic increase in AI projects
Organizations continue to unlock unprecedented value from a growing number of machine learning use cases that range across one or many departments and domains. According to IDC research spending by governments and businesses on AI will top $500 billion next year, with businesses applying AI across all industries. However, this growth in adoption has also uncovered new challenges, ranging across duplicated efforts, significant cost overheads and unmanaged compliance risk, among others. These challenges have restricted the full potential of organization-wide ML capabilities – that is, until now.
Value across a variety of industries
In terms of value, our customers measured 82% productivity gains on average when deploying models. Since launching Seldon Deploy in January 2021, we’ve seen a 5x increase in enterprise customers across industries – healthcare, FSI, automotive, technology, energy, retail, consulting, government, and defense. We see a lot of early adoption from regulated industries with advanced compliance requirements. This is especially true in industries such as Financial Services for example, where it is smart to be proactive about regulations so they are ready for when they are enforced by law.
Research is at the forefront of our MLOps journey
In 2022 we have invested in and strengthened our collaboration with the University of Cambridge, resulting in cutting-edge research driving new functionality like Multi-model serving with overcommit and data-centric pipelines. This is a giant leap forwards in empowering Data Scientists, ML Engineers – and ML teams to deploy, monitor, explain, and manage their ML models. In the product releases announced in the launch last week, we laid out how our entire stack has been rebuilt from the ground up, including next generation data-centric models serving via Core V2. This would have not been possible without our commitment to research and pushing the boundaries of possibility in this space.
Championing our open-source community
Another aspect of Seldon that has gone from strength to strength this year is our open source community. We’ve ramped up our in-person MLOps meetups, improved the content we’ve created and cultivated a thriving environment on our slack channel. Our open source community is essential to both the quality of our technology and the product roadmap. By the end of this year, we have hit 130k Monthly active unique nodes across 10k unique active clusters – that’s about 10x growth since last year!
Looking forward to 2023, we have so many things to be excited for at Seldon, I’m particularly excited to see those Open Source monthly active nodes and clusters ramping up after we release Core V2.
I love talking to our customers and users, so I’m looking forward to hearing from new customers in 2023 and what they are achieving with Seldon powering their Machine Learning.