These days, the concept of “observability” is gaining popularity within IT circles. It primarily involves monitoring a company’s systems to detect and address issues promptly as they arise, preventing potential disruptions such as website slowdowns or outages.
While many businesses are already working towards tackling this challenge, Flip AI is introducing a unique perspective. This early-stage startup has developed its own sophisticated language model to tackle the surveillance issue effectively.
In a recent announcement, the company revealed that its product is now available to the public, accompanied by an undisclosed $6.5 million seed investment.
Corey Harrison, the CEO and co-founder, highlighted that despite the plethora of available tools, many businesses still rely on conventional processes to track data flow between systems. Recognizing this gap, Harrison, along with his co-founders CTO Sunil Mallya and CPO Deap Ubhi, saw an opportunity to leverage technology and expertise to expedite issue resolution.
Harrison emphasized to TechCrunch that large corporations often face challenges in efficiently resolving issues despite using multiple tools. This struggle is particularly pronounced in larger companies with diverse data sources spread across various systems, complicating the root cause identification process.
Their innovative approach involves utilizing a substantial language model trained on DevOps data, encompassing over 100 billion tokens of specialized information like files, metrics, traces, and configurations. Harrison underscored that their model is proprietary and distinct from platforms like OpenAI, enabling a more human-like interrogation between systems.
The outcome is a tool capable of analyzing data from disparate systems and generating root cause analyses in under a minute, often within seconds. Harrison noted that their process retains the data in its original state, requiring minimal intervention to complete the analysis.
While Harrison acknowledges that no tool can guarantee absolute accuracy, he emphasized the transparency of their model’s decision-making process. This transparency allows human developers to review the conclusions reached, facilitating error localization and data collection, streamlining the debugging process significantly.
Despite the bold and innovative approach of Mallya and Ubhi in developing their proprietary language model, both individuals bring valuable experience from their roles as product management directors at Amazon Comprehend. Harrison, with a background in professional sports operations, adds a unique perspective to the team.
Currently, Flip AI operates with a team of twenty employees split between Bangalore, India, and San Francisco. As the company expands, Harrison aims to maintain a balance between operational efficiency and meeting customer demands. He also recognizes the importance of diversity in the tech industry, striving to ensure that Flip AI fosters an inclusive environment reflective of his own experiences and values.
The $6.5 million seed investment was led by Factory, with contributions from Morgan Stanley Next Level Fund and GTM Capital.
