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Flip AI Launches Observability Intelligence Platform

Flip AI launched with its observability intelligence platform, Flip, powered by a large language model (LLM) that predicts incidents and generates root cause analyses in seconds.

“When enterprise software doesn't perform as intended, it directly impacts customer experience and revenue. Current observability tools present an overwhelming amount of data on application performance. Developers and operators spend hours, sometimes days, poring through data and debugging incidents,” said Corey Harrison, co-founder and CEO of Flip AI. “Our LLM does this heavy lifting in seconds and immediately reduces mean time to detect and remediate critical incidents. Enterprises are calling Flip the ‘holy grail’ of observability.”

“We see in our research that observability, particularly incident resolution, is still in its early stages and remains a significant pain point for enterprises of all sizes. In fact, we see that 36% of respondents indicate they are planning to implement in the next 12-24 months,” said Paul Nashawaty, principal analyst at Enterprise Strategy Group. “Flip AI brings a refreshing and novel approach that is poised to transform observability and generative AI, as a whole.”

Flip automates incident resolution processes, reducing the effort to minutes for enterprise development teams. Flip’s core tenet is the notion of serving as an intelligence layer across all observability and infrastructure data sources and rationalizing through any modality of data, no matter where and how it is stored. Flip sits on top of traditional observability solutions like Datadog, Splunk and New Relic; open source solutions like Prometheus, OpenSearch and Elastic; and object stores like Amazon S3, Azure Blob Storage and GCP Cloud Storage. Flip’s LLM can work on structured and unstructured data; operates on-premises, multi-cloud and hybrid; requires little to no training; ensures that an enterprise’s data stays private; and has a minimal compute footprint.

“Software vendors of all types use generative AI to guide users and enrich products,” said Kevin Petrie, vice president of research at Eckerson Group. “Flip AI takes things a step further by using a language model to derive insights from multiple observability tools and explain their implications to users. This approach can simplify the work of ITOps engineers and speed their time to issue resolution.”

Flip AI also announced $6.5 million in seed funding led by Factory. Morgan Stanley Next Level Fund and GTM Capital also participated. The company plans to use the money to continue to advance its product roadmap and LLM and to expand its team and operations.

"Flip AI is a world-class team with deep AI and enterprise experience. They are industry veterans when it comes to building next level customer experiences for enterprises. Their large language model, the first in the world for DevOps, is a breakthrough in generative AI and sets a new standard in observability for years to come," said Andy Jacques, CEO and managing partner at Factory.

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Flip AI Launches Observability Intelligence Platform

Flip AI launched with its observability intelligence platform, Flip, powered by a large language model (LLM) that predicts incidents and generates root cause analyses in seconds.

“When enterprise software doesn't perform as intended, it directly impacts customer experience and revenue. Current observability tools present an overwhelming amount of data on application performance. Developers and operators spend hours, sometimes days, poring through data and debugging incidents,” said Corey Harrison, co-founder and CEO of Flip AI. “Our LLM does this heavy lifting in seconds and immediately reduces mean time to detect and remediate critical incidents. Enterprises are calling Flip the ‘holy grail’ of observability.”

“We see in our research that observability, particularly incident resolution, is still in its early stages and remains a significant pain point for enterprises of all sizes. In fact, we see that 36% of respondents indicate they are planning to implement in the next 12-24 months,” said Paul Nashawaty, principal analyst at Enterprise Strategy Group. “Flip AI brings a refreshing and novel approach that is poised to transform observability and generative AI, as a whole.”

Flip automates incident resolution processes, reducing the effort to minutes for enterprise development teams. Flip’s core tenet is the notion of serving as an intelligence layer across all observability and infrastructure data sources and rationalizing through any modality of data, no matter where and how it is stored. Flip sits on top of traditional observability solutions like Datadog, Splunk and New Relic; open source solutions like Prometheus, OpenSearch and Elastic; and object stores like Amazon S3, Azure Blob Storage and GCP Cloud Storage. Flip’s LLM can work on structured and unstructured data; operates on-premises, multi-cloud and hybrid; requires little to no training; ensures that an enterprise’s data stays private; and has a minimal compute footprint.

“Software vendors of all types use generative AI to guide users and enrich products,” said Kevin Petrie, vice president of research at Eckerson Group. “Flip AI takes things a step further by using a language model to derive insights from multiple observability tools and explain their implications to users. This approach can simplify the work of ITOps engineers and speed their time to issue resolution.”

Flip AI also announced $6.5 million in seed funding led by Factory. Morgan Stanley Next Level Fund and GTM Capital also participated. The company plans to use the money to continue to advance its product roadmap and LLM and to expand its team and operations.

"Flip AI is a world-class team with deep AI and enterprise experience. They are industry veterans when it comes to building next level customer experiences for enterprises. Their large language model, the first in the world for DevOps, is a breakthrough in generative AI and sets a new standard in observability for years to come," said Andy Jacques, CEO and managing partner at Factory.

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Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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