Meet Sola Security: the enterprise security brain behind the agentic era

Artificial intelligence is changing how enterprise security teams operate. Tasks that once required analysts to spend hours investigating alerts, correlating data, and navigating different security platforms are increasingly being delegated to AI copilots and autonomous agents.

Yet as organizations accelerate adoption, a fundamental question remains: how effectively can an AI agent protect an environment it does not fully understand?

Enterprise networks are complex ecosystems spanning cloud infrastructure, endpoints, identity systems, SaaS applications, and interconnected security products. The information needed to understand them is scattered across technical platforms, internal documentation, policies, incident reports, and operational workflows.

For AI to become genuinely useful in cybersecurity, access to data alone is not enough. It needs the context to understand how everything connects.

This is the challenge Sola Security is addressing. The company is building what it calls an enterprise security brain: a unified, vendor-agnostic context layer designed to give security teams and AI agents a shared understanding of their entire environment.

Why AI agents still struggle with cybersecurity

The development of large language models and autonomous agents has created expectations that security operations could become substantially more automated. However, applying these technologies to enterprise environments introduces challenges that go beyond the capabilities of individual models.

Ron Peled, Co-Founder and COO of Sola Security, believes the industry’s biggest misconception is that intelligence alone is enough to make AI effective in cybersecurity.

“LLMs are good with text, coding agents are amazing with code, but security isn’t just text and definitely not just source code,” Peled explains. “Security is about relationships, dependencies, connections, and much more.”

The difficulty starts with fragmented information. Security teams must interpret data from numerous products while accounting for organizational knowledge that rarely exists within those platforms. Documents, policies, procedures, contracts, reports, and tickets all contribute to understanding an organization’s security posture, yet AI agents frequently operate without access to this context.

Even centralized data lakes and security information and event management (SIEM) platforms can provide incomplete or noisy representations of the environment. Meanwhile, individual security vendors are introducing their own copilots and agents, each working with a limited view of the organization’s infrastructure. As Peled explains, “They only see a part of it.”

Consequently, even sophisticated AI systems can struggle to produce reliable answers when they cannot connect information across the broader enterprise.

Building a shared security brain

Sola’s approach is to address this context problem at the infrastructure level. Rather than introducing another isolated security product, the company is developing a unified layer that connects information across an organization’s existing tools and systems.

The platform functions as a vendor-agnostic enterprise security brain, bringing together technical information and organizational knowledge to create a continuously maintained understanding of the environment. Security teams and AI agents can then consume this validated intelligence through their existing workflows.

Sola’s differentiator lies in combining organizational context, security research, and the pre-computation of high-priority intelligence. Rather than waiting for a question or an agent request, the platform continuously identifies and prepares the most relevant information, making it available proactively or on demand, wherever and whenever security teams need it.

Importantly, organizations do not need to replace their current security infrastructure to adopt Sola. The platform is designed to work with existing products and data sources, connecting information that would otherwise remain fragmented across different systems.

Its coverage spans cloud environments, endpoints, identity systems, SaaS applications, and coding agents. By understanding individual entities alongside their relationships and dependencies, Sola aims to answer complex security questions that would otherwise require analysts to investigate multiple platforms and manually correlate findings.

Consistency, governance, and cost efficiency

A shared understanding of the enterprise also has implications for how organizations govern and scale AI deployments. When different agents independently retrieve and interpret information, their answers can vary depending on which systems they access. Sola instead aims to provide a consistent intelligence foundation, with answers grounded in evidence from across the environment.

Its architecture also addresses the security implications of autonomous systems. Rather than giving multiple homegrown agents their own production credentials, organizations can use Sola as a governed, read-only intelligence layer. This provides AI systems with the context they need without unnecessarily expanding their operational permissions.

There is also an economic consideration. Repeatedly asking AI models to explore systems, retrieve information, and reconstruct organizational context consumes tokens and analyst hours. Sola says its approach can reduce AI queries by approximately 70% by building and maintaining context centrally, rather than recreating it for every request. The company also positions this model as a way to avoid staffing a dedicated context-engineering team.

Testing the future of autonomous security

Beyond its platform, Sola is investing in research around how AI agents perform in realistic enterprise security conditions. Through its research initiatives and Open.Security, the company examines how agents reason, where they fail, and whether their outputs can be trusted.

This addresses an increasingly important question for security leaders: as more responsibilities move from human analysts to autonomous systems, how can organizations establish confidence in the decisions those systems make? Understanding an agent’s capabilities is only part of the equation; understanding its limitations and the evidence behind its conclusions is equally important.

For Peled and the Sola team, the underlying principle is straightforward. “No matter how smart or powerful the AI model is, without your unique organisational context and knowledge, it will keep struggling, draining time, budget, or both,” he says.

As enterprises move toward increasingly autonomous security operations, the next competitive advantage may not come exclusively from deploying more powerful models or adding more agents. It may come from the infrastructure that allows those systems to understand the organization as a whole. Sola Security is building around that premise, positioning the enterprise security brain as a foundational layer for the agentic era.