Creating cutting-edge AI technology for intricate cloud-native systems: Introducing NeuBird

NeuBird founders Goutham Rao and Vinod Jayaraman came from PortWorx, a cloud native storage solution they eventually sold to PureStorage in 2019 for $370 million. When they went looking for their next startup challenge last year, they saw an opportunity to combine their cloud native knowledge, especially around IT operations, with the burgeoning area of generative AI. Rao, the CEO, says that while the cloud native community has done a good job at solving a lot of difficult problems, it has created increasing levels of complexity along the way. “We’ve done an incredible job as a community over the past 10 plus years building cloud native architectures with service oriented designs. At the same time, large language models were beginning to mature, so the founders decided to put them to work on the problem.

NeuBird is the brainchild of Goutham Rao and Vinod Jayaraman, the founders who previously launched and sold PortWorx for a whopping $370 million to PureStorage in 2019. This was their third successful exit, and it left them seeking out their next startup challenge.

Coming from a background in cloud native storage solutions, the duo saw an opportunity to merge their expertise in this field with the growing trend of generative AI. And today, Mayfield announced a $22 million investment in Neubird to help bring their idea to the market. While this may seem like a hefty amount for an early stage startup, the firm is likely banking on the founders’ proven track record in building successful companies.

In a recent interview with TechCrunch, CEO Rao expressed that while the cloud native community has made great strides in solving complex problems, it has also added layers of complexity along the way. He stated, “We’ve done an incredible job as a community over the past 10 plus years building cloud native architectures with service oriented designs. This added a lot of layers, which is good. That’s a proper way to design software, but this also came at a cost of increased telemetry. There’s just too many layers in the stack.”

This overwhelming amount of data has made it nearly impossible for human engineers to effectively and efficiently find, diagnose, and solve problems at scale, especially within large organizations. That’s where Neubird comes in.

“We’re leveraging large language models in a very unique way to be able to analyze thousands and thousands of metrics, alerts, logs, traces and application configuration information in a matter of seconds and be able to diagnose what the health of the environment is, detect if there’s a problem and come up with a solution,”

– Goutham Rao, CEO of Neubird

The team at Neubird is essentially creating a trusted digital assistant for engineering teams. Rao explains, “So it’s a digital co-worker that works alongside SREs and ITOps engineers, and monitors all of the alerts and logs looking for issues.” Their ultimate goal is to reduce the amount of time it takes to respond to and solve an incident from hours to minutes, and they believe that by harnessing the power of generative AI, they can help companies achieve this goal.

Neubird’s founders are well aware of the limitations of large language models and are taking precautions to minimize hallucinated or incorrect responses. They are doing this by using a limited set of data to train the models and setting up various systems to ensure more accurate results.

Rao explains, “Because we’re using this in a very controlled manner for a very specific use case for environments we know, we can cross check the results that are coming out of the AI, again through a vector database and see if it’s even making sense and if we’re not comfortable with it, we won’t recommend it to the user.”

To connect with their various cloud systems, customers can simply enter their credentials without having to worry about moving data. Neubird is able to use this access to cross check against other available information and provide a solution, ultimately reducing the difficulty associated with obtaining company-specific data for the model to work with.

The company utilizes various models, such as Llama 2 for analyzing logs and metrics, and Mistral for other types of analysis. In fact, every natural language interaction is turned into a SQL query, effectively transforming unstructured data into structured data and resulting in greater accuracy.

Currently, Neubird is working with design and alpha partners to refine their idea, with plans to bring the product to market later this year. Rao explains that they took a significant amount of funding from the start to give them room to work on the problem without having to worry about seeking more money too soon.

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Max Chen

Max Chen is an AI expert and journalist with a focus on the ethical and societal implications of emerging technologies. He has a background in computer science and is known for his clear and concise writing on complex technical topics. He has also written extensively on the potential risks and benefits of AI, and is a frequent speaker on the subject at industry conferences and events.

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