Who's Observing The Observers—Cleaning Up The AI Mess In Aisle Seven

Forbes

a day ago

Today's news, that Coralogix closed a $115M funding round at a $1B valuation to disrupt observability with agentic AI, made we wonder — shouldn't C-Suite Leaders know who is observing the observers?
For some, it's been exciting to watch AI progress at lightning speed over the past few years. For others, the pace is exhausting, including those covering it, enterprises aiming to put it to productive work, and vendors striving to develop the tech or integrate it into their stacks.
Investors have been pouring in money at an impressive rate. A Crunchbase report documented the rise in startup funding last year which was dominated by investments in AI. According to their data: 'Close to a third of all global venture funding went to companies in AI-related fields, making artificial intelligence the leading sector for funding. Funding to AI-related companies reached over $100B — up more than 80% year over year from $55.6B in 2023.'
About a third of this went to foundation model companies. The rest flowed to related sectors like IT infrastructure needed to run AI, and those segments that rely on AI: autonomous vehicles, healthcare, robotics, etc. Want details? Stanford University reported that GenAI funding soared in 2024. Look for these numbers to jump again, with a continued march of funding rounds and M&A deals ahead.
These trends are probably not surprising. After all, even though the category has seen strong investments over the last ten years, close to $.5T, AI innovation presents a major inflection that is having a ripple effect across most all sectors. And GenAI and LLMs are the poster kids for the leaps we are seeing.
But news from IT observability vendor Coralogix, about a $115M E Round at +$1B valuation, showed that some smart money is finding its way to the technology needed to manage the mess we are creating. Yes, there can be some delight at the nexus of the less sexy areas of IT performance and AI safety - both of which are linchpins to further maturation and adoption of AI in the enterprise.
Why Observing The Observers Really Matters
The news relates to an area of IT that some may not be familiar with; so, I'll explain. Observability is the ability to understand the state of a system by examining the data it generates. The tech emerged from the software engineering and network monitoring worlds, as a response to the challenges of managing increasingly complex environments driven by the growth of cloud and distributed computing.
Basically, what it does is hoover in all the data 'exhaust fumes' generated by logs, metrics and traces, to make better sense of what is happening and help site reliability engineers (SREs) reduce outages and improve system health and reliability. The technology has evolved to take on more tasks, including application performance monitoring and security - encroaching on these spaces and sometimes integrating with the technologies.
Today, IT observability is a dynamic, highly competitive, and rapidly growing segment of enterprise IT. According to Gartner, the market is expanding at a compound annual growth rate (CAGR) of over 15%, with projections placing its total size at around $11.2 billion by 2026
I said that its evolution is a result of growing IT complexity and that AI adds an inflection, and some would argue, more complexity to the enterprise. At the same time, we all know that AI can help in managing things and drive better understanding of complex issues. What happens when AI meets observability?
Taking On The Big Dogs Of Observability
This brings us to today's news, which is a shot across the bow by Coralogix against the big dogs, not just metaphorically but also literally: e.g., Datadog, Dynatrace, New Relic, AppDynamics, Splunk and Acceldata.
These vendors help manage AI and use some form of it (e.g., machine learning or LLMs) in their stacks. They are also bullish about combining AI and observability. For example, on recent earning calls, Datadog CEO Josh Pomel said, "We continue to see rising customer [demand]
It seems Coralogix is taking a more aggressive approach. The company acquired AI observability provider Aporia last year, which resulted in the launch of their AI Center; the first solution to treat AI as a separate observability stack. Their AI Center helps manage not only AI performance, as some others do, but also its content, enabling businesses to detect hallucinations, toxicity, prompt injection (yeah that's a thing), and more.
Now, Coralogix has secured a major investment that should fuel its drive to disrupt the space with the first AI agent that extends observability value across the enterprise.
Why is this significant to C-Suite Leaders? First, from a sheer numbers PoV, it is a big round. While not the largest in AI by any stretch, it is an impressive amount for an up-and-comer that is not aiming to move mountains in the capital-intensive LLM and chips arenas.
I spoke with Coralogix CEO Ariel Assaraf about the news and their current status. He did not provide hard revenue numbers but said that the company has achieved impressive 72% YoY growth for the last three years. Customers include well-known logos like Adobe Systems, Ferrari and DoorDash.
This round was led by CA-based venture growth firm NewView Capital. Ariel shared that all existing investors including Advent International, Brighton Park Capital, Revaia, and Greenfield Partners, returned to support Coralogix's continued growth and launch into agentic AI observability.
'Decoder Ring' Knocks Down Tower Of Babel Separating Business And IT
Interestingly, they issued a second and related announcement at the same time: 'Coralogix Unveils Industry's First AI Agent That Extends Observability Value Across the Enterprise.'
When I asked Ariel Assaraf to connect the dots; he said: "We have this unique architecture that allows teams to ingest more data, analyze the data in-stream, and make informed decisions for optimization. Traditional observability is super-expensive and doesn't scale; we fixed that. Now we're adding agentic AI, and people can make informed decisions across business units without being experts."
He further explained: "AI introduces new challenges around data security, accuracy, and scale, demanding a new approach. Agentic AI can enable smarter observability that minimizes manual effort and makes it easier for teams to surface and act on insights from their data.'
According to the press release, their agent, called 'Olly,' is an agentic AI that transcends the more typical event alerts observability platforms generate to answer questions and provide guidance.
This sounds like they are tackling the disconnect that can occur between the business and IT sides. It's the old business and IT alignment challenge that has yet to be solved. One of the biggest barriers is the translation gap — non-technical stakeholders can't easily understand 'geek speak' or explore how backend systems impact business outcomes.
With Olly, both technical and non-technical users can ask questions in plain English, from 'What is wrong with the payment flow?' or 'Why do some users struggle with logging in?' to more holistic questions like 'Which service is frustrating our users the most?' In short, democratizing insights available from observability, to better connect IT performance and drive smarter outcomes, is what enterprises need now.
As AI-enabled observability becomes more mainstream in the enterprise, look for impacts across the organization — from frontline performers to boardroom risk mitigators. Like other tech trends I've unpacked, which are critical for the next generation of C-Suiters to lead their organizations, keep an eye on the observers to help you better align the tech and business goals — and hopefully boost results across your enterprise.