A Modern Data Architecture to Drive Next-Gen AI

Attackers Move at AI Speed, Shouldn't Your Security?

In today's rapidly evolving threat landscape, managing vulnerabilities using static databases and periodic reports is dangerously outdated. Enterprises face not only traditional threats but AI-driven attacks that evolve in real-time, necessitating an equally agile defense.

At Cogent, we’ve embraced stream processing and real-time AI as core strategic investments. Why? Because in an AI-native world, your defenses must adapt faster than adversaries.

The Pain Today: Massive Scale, Missing Context, Mounting Risk

Vulnerability management today is increasingly subject to pain points that traditional tools can’t solve:

• Massive Data Scale: Enterprises face millions of vulnerabilities across tens of thousands of assets. Security teams are overwhelmed by alerts, struggling to isolate real risks. Manual triage is impossible at this scale while critical issues slip through the cracks.

• Poor Data Quality, Context Lost in Translation: CMDBs quickly become outdated or incomplete, and siloed tools store mismatched data, causing duplication and confusion. A CVE number alone doesn’t reveal true risk, it's the asset's sensitivity, exposure, and existing controls (often scattered or missing) that determine impact.

• Operational Drift: Workflows are brittle. Scans are exported, spreadsheets assembled, tickets created by hand. By the time that reports are shared, the environment has shifted. This drift delays response and undermines confidence.

The result? Security teams are flying blind. Fragmented data and broken workflows produce slow, incomplete, and error-prone decisions while their organizations face increasing risk from attackers who move with ever more sophistication and speed.

Why Legacy Approaches Fall Short

Legacy solutions weren’t built for real-time, context-rich inference and operationalization. They struggle to keep up with today’s demands.

Static CMDBs are incomplete and decay quickly in dynamic cloud and DevOps environments. Point solutions don’t integrate or share context, requiring security teams to stitch together dashboards manually, wasting time and missing the bigger picture. Generic risk prioritization doesn't factor in business context, and becomes noise. A test server vulnerability may be treated as critical, while a production risk goes unnoticed.

These systems and processes were designed for a different era. Today’s security teams need agility, automation, and actionable intelligence.

Cogent’s AI Fabric: The Brain That Learns By Itself

Cogent Security was developed to address a common challenge: bringing together dispersed security data into a continuously updated system that provides a clear, actionable view of your operations.

Real-Time Ingestion

Cogent continuously ingests data from scanners, CMDBs, cloud platforms, and more. No more waiting for batch reports — changes are reflected instantly.

Unified Environment Topology

All incoming data is normalized into a knowledge graph that maps assets, vulnerabilities, business functions, ownership, controls, and other functions. The result: a living, searchable model of your environment.

AI-Driven Context Enrichment

As data flows in, Cogent applies rules, heuristics, and uses language models to assess exploitability, predict business impact, and classify asset sensitivity. This allows us to inform real-time understanding and action.

Built for Speed, Designed for Scale

Cogent’s platform is built on a streaming-first foundation because we believe it’s absolutely necessary in this AI-native era. In today’s threat landscape, batch processing is too slow and static data models are too brittle. Threats don’t wait, and neither should your response.

Native Stream Processing

Cogent’s streaming-first architecture enables real-time processing, correlation, and decision-making across billions of signals. This means vulnerabilities can be identified, contextualized, and prioritized as they happen, not hours or days later. Every change, from vulnerabilities to asset updates, instantly becomes actionable intelligence.

AI-driven Entity Resolution

Advanced language models autonomously resolve identities and reconcile conflicts as data streams in, continuously and at scale.

Semantic Understanding at Scale

Enterprise knowledge (from Jira tickets to system logs) is indexed and searchable in real-time, turning scattered context into strategic insights.

Data → Insight → Action

Understanding risk is half the battle. Acting on it is where most platforms stall. Cogent changes that with our unique approach.

Event-Driven Architecture

Every change, a new vulnerability, an asset update or a new employee onboarding, becomes an event in a live stream. Cogent reacts instantly, triggering workflows the moment something relevant occurs.

AI Agents

Domain expert AI agents subscribe to these events and automate decisions: open tickets with full context, trigger network segmentation if exposure is detected, escalate crown jewel issues with urgency.

Closed-Loop Feedback

Actions (like remediation or exception approvals) are written back to the knowledge graph. Risk scores update. Dashboards reflect the latest state. The system improves continuously based on outcomes, completing a true DevSecOps feedback loop.

Together, real-time data and AI agents transform static workflows into dynamic, intelligent operations.

Powering Next-Gen AI with Cogent’s AI Fabric

Cogent’s AI Fabric is more than a data pipeline, it’s the foundation that powers next-generation AI for security. By streaming every vulnerability, asset update, and event into a unified knowledge graph, it turns scattered data into real-time intelligence. This means you can see your entire environment in one place, let AI prioritize the vulnerabilities that truly matter, and automate remediation steps with confidence and intelligence.

When attackers move at AI speed, you need a data architecture that does the same. Cogent’s AI Fabric drives smarter, faster defenses by constantly learning from your live data and acting on it. It’s how you go from reactive firefighting to proactive, AI-powered security.