Expanding the Foundation of AI-Native SOCs: Mastering Holistic Data Integration

As highlighted in our previous blog, Building an AI-Native Security Operations Center (SOC), Holistic Data Integration is the first cornerstone of modern security operations. Without it, even the most advanced AI tools and automated processes can fall short. In this follow-up, we delve deeper into the evolving role of telemetry as the foundation for holistic data integration. Telemetry has long been the unsung hero of security operations, providing raw signals from systems, applications, and endpoints. Yet, for many organizations, it remains fragmented—scattered across tools, obscured by noise, and disconnected from broader strategies.

In an AI-native SOC, this piecemeal approach is no longer viable. Telemetry must evolve from raw, disjointed data streams into a unified, context-rich foundation for security decision-making. This evolution is not about collecting more data; it’s about strategically integrating and transforming that data to power actionable intelligence. This new perspective is encapsulated in Telemetry-First Design and Telemetry as a Platform (TaaP)—two visionary concepts that are set to redefine security operations.

Telemetry-First Design

Telemetry, at its core, refers to the automated collection, transmission, and analysis of data from systems, devices, or applications. In the context of security operations, telemetry includes logs, metrics, and events generated by networks, infrastructure and applications. Imagine building a skyscraper without first ensuring the foundation is solid. That’s what a security strategy looks like when telemetry is treated as an afterthought. Telemetry-First Design flips this approach on its head by prioritizing the collection, normalization, and contextualization of data before any Automation tools or AI models are implemented.

This vision requires a mindset shift:

Prioritize completeness over convenience. Every potential telemetry source, from networks, infrastructure and applications must be captured and integrated.

Focus on context, not just content. Raw signals must be enriched with metadata that provides business, user, and system context, transforming them into insights.

Ensure interoperability. Breaks down silos, enabling data to flow seamlessly across AI models, automation systems, and human analysts.

This proactive approach ensures that the SOC operates with comprehensive, real-time visibility, creating a solid foundation for all subsequent processes in an AI-Native SOC.

Telemetry as a Platform (TaaP)

As organizations adopt Telemetry-First principles, the next strategic frontier emerges: Telemetry as a Platform (TaaP). TaaP represents the culmination of a mature data integration strategy, where telemetry is no longer treated as a static resource but as an active enabler of the SOC’s capabilities. TaaP is not just about centralizing data; it’s about building an intelligent, scalable data lake platform that serves as the operational backbone of the SOC.

With TaaP, this approach is fundamentally reimagined:

Unified Insight: TaaP aggregates telemetry across all sources—internal systems, external feeds, and partner ecosystems—into a single, actionable narrative.

Dynamic Adaptability: It evolves in tandem with the business context, seamlessly integrating new data streams and responding to emerging threats.

Empowered Decision-Making: By embedding AI and automation directly into the platform, TaaP enables decisions that are faster, smarter, and more precise than ever before.

Rethinking Security Operations Strategy with TaaP

By aligning telemetry with AI, TaaP not only accelerates detection and response but also provides confidence in the organization’s ability to adapt to even the most unpredictable threats.

To illustrate the transformative power of Telemetry as a Platform (TaaP), consider the challenge of detecting and mitigating insider threats. Traditionally, this process relies on multiple tools working in isolation to analyze user activity, HR records, and endpoint logs. This fragmented approach creates delays, blind spots, and inefficiencies, as analysts must manually piece together insights from disparate systems. With TaaP, telemetry from all relevant sources is ingested into a unified platform, enabling seamless data integration.

Advanced AI models are then allowed to analyze patterns across this comprehensive dataset in real time, identifying unusual behaviors that might signal malicious activity. These insights are immediately operationalized through automated workflows, isolating suspicious actions and alerting security teams within seconds. This cohesive, data-driven strategy not only accelerates detection and response times but also enhances accuracy, reducing false positives and dramatically improving operational efficiency.

Adopting TaaP for AI-Native SOCs

Adopting a Telemetry-First mindset and transitioning to TaaP is not about chasing the latest technology trends. It’s about ensuring that your organization is positioned to thrive in an era where data is the most valuable resource. The journey to an AI-native SOC begins with a commitment to rethinking your approach to data. It’s about recognizing telemetry as a strategic asset and investing in its potential to unlock new levels of efficiency, intelligence, and resilience.

As we move forward, the organizations that lead in security operations will be those that master the art of data integration, treating telemetry not just as information but as the foundation for a smarter, stronger, and more secure future. And as the lines between business strategy, technological evolution, and cybersecurity continue to blur, how can you ensure that your organization’s data infrastructure is not only a reflection of today’s needs but also a proactive force that anticipates tomorrow’s challenges, driving both security and strategic growth in an increasingly complex world of combining AI and security operations?

Cisco’s integration of Splunk has the potential to redefine the future of security and observability by establishing a cohesive data fabric that spans networks, infrastructure and applications. Acting as a universal telemetry backbone, this unified layer transforms fragmented data streams into actionable insights, enabling real-time threat detection, predictive analytics, and compliance automation. By bridging operational silos with advanced telemetry ingestion, correlation, and analysis capabilities, this evolution paves the way for multi-domain observability and AI-native security operations, setting a new standard for resilience and adaptability in modern digital ecosystems.

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