It’s 2025 and operational complexity has hit a breaking point.

Security, DevOps, and IT teams find themselves juggling hundreds of tools and apps, each addressing a narrow task. The result is often a fragmented ecosystem of dashboards, alerts, and workflows that barely talk to each other. It’s no wonder platformization (the drive to consolidate and integrate tools) has become a rallying cry in cybersecurity. But while consolidation is important, a lot of current platform solutions are just bloated SaaS bundles with an AI chatbot put on top.

There’s a better way to address this: an agentic AI-powered hub (like Kindo) that can truly unify operations with far fewer apps in play. In this article, we’ll explore the trend of security tool consolidation, why the typical enterprise’s 300+ applications are unsustainable, and how an AI-native, action-oriented platform can cut through the noise. If you’re a SecOps, DevOps, or ITOps leader at hyperscale, this is a conversation you can’t afford to ignore – operational efficiency is becoming a major issue.

The Push for Platformization and Tool Consolidation

Enterprise security strategy is undergoing a fundamental shift. For years, organizations kept adding point solutions for every new threat or compliance requirement. The typical large company ended up running over 300 different software applications (in fact, the average business uses 367 apps and systems). Each department or team deployed its own favorite tools. This best-of-breed approach had good intentions – specialization can mean depth – but in practice, it created a complex patchwork that is now cracking under its own weight. Security teams especially feel the pain. One recent study found organizations are juggling 83 security tools from 29 vendors on average.

The side effects of this tool sprawl have been severe:

1. Management complexity. Teams must maintain proficiency across dozens of interfaces and workflows, stretching human expertise thin.
2. Integration headaches. Point solutions rarely communicate or share data smoothly. Context is lost in translation (if things are integrated at all).
3. Alert fatigue. Analysts drown in disjointed alerts from each system, without a unified story. Important signals get lost in the noise.
4. Expanded attack surface. Every additional tool is another piece of software that could contain vulnerabilities, increasing risk.
5. Skyrocketing costs. Licensing, maintaining, and staffing expertise for many tools pushes budgets to the brink.

It’s no surprise that security leaders are saying enough. They’re now actively consolidating their vendor footprint – moving away from managing 30+ security vendors and instead opting for integrated platforms. The platformization trend means choosing a smaller number of comprehensive platforms (from providers like CrowdStrike, Palo Alto, Cisco, etc.) rather than a hodgepodge of point products.

An IBM/Palo Alto Networks study in 2025 found that companies who migrated to integrated security platforms saw four times greater ROI and spent less overall compared to those maintaining fragmented tools. Importantly, they also drastically cut the time to identify and mitigate breaches (by 74 and 84 days faster, respectively). In one real-world example, a financial firm trimmed its security vendors from 28 to 7 and reduced total security spend by 22%. Clearly, consolidation isn’t just an IT fad – it’s becoming a financial and operational imperative.

The “Chatbot Layer” Illusion

Yet, if consolidation is so great, why are enterprises still drowning in software? The truth is that SaaS sprawl has spread across all of IT, not just security. Businesses today use an average of 130+ SaaS tools across departments, and larger enterprises often far exceed that. One venture analysis noted an average enterprise “consumes over 300 SaaS applications at any one time” (with ~30% changing every year). This overload has real consequences: workers spend 2.4 hours per day searching for information across systems – nearly one-third of their work week – resulting in a 24% drop in productivity on average. In other words, the very tools meant to make us efficient have, in excess, made us inefficient.

So, consolidation does make sense – but how it’s done matters.

Many of the current “all-in-one” platforms are essentially big SaaS suites that bundle features from different acquisitions or modules. They promise to remove point-tool complexity, but often introduce a new kind of complexity: a monolithic cloud service with its own learning curve and bloat. And lately, every vendor is putting “AI” on their product, usually in the form of a chatbot or virtual assistant.

‍Add a fancy chat interface, and your old software is now ‘AI-powered’!

However, let’s be clear: putting a chatbot on top of a tangled stack doesn’t magically make it intelligent. Many AI-powered ops tools today simply add a conversational layer for querying data or automating simple tasks. They might answer questions or recommend actions, but they don’t fundamentally change the architecture beneath. In effect, the underlying complexity and siloed nature of the apps remain.

We’ve seen this play out at recent industry conferences (without naming names). Vendors showcase AI assistants that can reset a password or draft a security report via chat. Useful? Sure. But these are incremental improvements, not the autonomous ops revolution enterprises desperately need. The typical company still has to manage the 300-tool chaos in the background. All the chatbot does is provide a new front-end for the same old sprawl.

From Fragmented Tools to a Single Intelligent Hub

What’s the alternative? Well, instead of just papering over tool sprawl with a chatbot, forward-thinking teams are looking at AI-native automation platforms that serve as a central brain for operations. The idea is to create a unifying hub powered by agentic AI – AI that doesn’t just chat or recommend, but can act autonomously on your systems with proper guardrails. This is where Kindo comes into the picture as an example of this newer approach.

Unlike legacy platforms retrofitting AI into their products, Kindo was built AI-first from the ground up. It’s designed to be agentic, explainable, and secure by design, rather than AI being an afterthought. In practice, this means Kindo deploys intelligent agents that can autonomously make decisions and take actions in real time – not simply execute static scripts or wait for human approval.

An AI hub like this doesn’t force you to rip out all your existing systems overnight. Interoperability is key here. Kindo’s platform connects directly into the tools and layers you already use – Kubernetes clusters, cloud APIs, CI/CD pipelines, ITSM ticketing systems, security information and event management (SIEM) tools, even HPC job schedulers like Slurm. It acts as a connective tissue, orchestrating end-to-end processes that previously required multiple manual handoffs.

To give you an example, imagine a typical incident workflow: a SIEM generates a security alert, an engineer digs through Git commits for recent changes, ops might isolate an affected container in Kubernetes, and perhaps an analyst runs a diagnostic job on the HPC cluster to validate a patch. In a traditional setup, that’s several teams and tools involved. In a Kindo-like setup, an AI agent can handle that entire chain automatically – cross-referencing the alert with code changes, isolating the Kubernetes pods, scheduling a Slurm job to verify the fix, and even documenting the steps for compliance – all without human intervention.

Security and trust are naturally top of mind when you empower AI to take actions. These agentic platforms are built with strong guardrails: role-based access control, audit logs of every action, policy constraints, and human approval checkpoints where needed. The goal is autonomous operations with oversight – you trust the AI to handle routine tasks, but you can always trace why it did something and constrain what it’s allowed to do. Done right, this actually enhances security (fewer chances for human error or oversight gaps) while freeing your experts to focus on high-level strategy rather than firefighting.

For SecOps, DevOps, and ITOps teams, using an AI-native hub can feel like adding a central nervous system to your environment. Instead of a dozen disparate tools each blinking their own warnings, you get an intelligent platform that understands the bigger picture and coordinates the response. Kindo’s vision is exactly that: to be the intelligent core automating SecOps, DevOps, and ITOps for companies that simply cannot afford inefficiency at scale.

Start Now or Be Left Behind

Based on everything above, the writing on the wall is clear: consolidate your operations stack, or risk being outpaced by those who do. This is not about minor tweaks or trimming a little budget – it’s about rethinking how we run technical operations at a fundamental level.

Instead of 10 different tools for automation, monitoring, and incident response, you might have one integrated AI platform coordinating it all. Instead of every team purchasing its own SaaS app for every problem, you extend the brainpower of one central AI-driven system into each domain. Early adopters consolidating in this way have already seen order-of-magnitude improvements in ROI and productivity. Imagine your enterprise in 2027 running on 20% of the apps you use today – lean, cohesive, and largely self-managing.

‍It’s a vision worth fighting for.

We’re at a crossroads where simply buying more tools is not the answer. Platformization must be done in an intelligent way – not just bundling, but truly integrating and automating. The rise of agentic AI hubs offers a path to do exactly that. It’s both a technical and a philosophical shift: trusting AI-driven automation as a core feature of operations, not as a fancy overlay. For enterprises operating at scale, whether in the cloud or on-prem GPU farms, this is nothing short of an evolution in how we work. Consolidation with agentic AI isn’t about sacrificing capability – it’s about eliminating the needless friction between capabilities. It’s about having one brain where there used to be hundreds of isolated parts. The future of cybersecurity and infrastructure operations will belong to those who simplify and automate. So ask yourself:

‍Will you still be wrangling 300+ tools by 2027, or will an AI-powered central platform be doing the heavy lifting?

The choice, and the future, is yours to shape. Embrace the agentic AI revolution and turn today’s sprawling toolbox into tomorrow’s coordinated powerhouse. Your teams (and your bottom line) will thank you.

‍To get started with all of this, request a demo and find out how we can help you.