Tel Aviv-based artificial intelligence monitoring platform Aporia has left stealth mode today and announced their $5 million seed funding in an effort to ensure AI integrity.
Led by Vertex Ventures and TLV partners, angel investors Yevgeny Dibrov & Nadir Izrael, founders of Armis, Gili Ra'anan, a General Partner at CyberStarts and Sequoia, and Michael Shaulov, Founder & CEO of Fireblocks also participated in the raise.
“AI adoption is soaring and requires a proper technological stack to handle the new challenges that come with it. Aporia is a vital part in the new MLOps stack, filling a critical gap in production readiness of AI," comments Emanuel Timor, General Partner at Vertex Ventures.
The common expression, “Nobody’s perfect,” is perfectly acceptable when it comes to human beings. However, when artificial intelligence isn’t perfect, we’ve seen things go, well, let’s say, “awry.”
Aporia’s service allows data scientists to create their own parameters to monitor machine learning models. Theoretically, this should ensure data integrity and ensure that AI stays on track and on task.
For all the attention that machine learning has garnered in recent years, Forbes reports that the vast majority of the $50+ billion being invested in the space is largely unmonitored. This lack of observation can lead to a number of unintended consequences, thus undermining the significant amount of time and money invested.
For all the near-perfection that machine learning can deliver, it still relies on variables in order to make predictions. These variables, some of which include real-world, i.e. human-generated, data can reap havoc within the system. Changes to databases and APIs, world events (did someone say COVID-19?), and even expanding into a new market, can all cause an intended programme to drift. This drifting over time can leave to lost revenues and potential legal issues for businesses.
Aporia wants to eliminate these losses before they even begin to happen.
“AI needs guardrails. Companies need to have confidence in their machine learning models, and the only way to get there is by robust monitoring to ensure they’re doing what they’re supposed to do,” says Aporia CEO Liran Hason. “Aporia makes monitoring simple, fast and secure, bringing engineering and DevOps best-practices into the new field of MLOps and ensuring that data science teams can keep their models performing accurately and fairly.”