Five Ways Exabeam Delivers Better Detection and Security Outcomes Than Microsoft Sentinel

SIEM platforms play a central role in detecting and investigating threats. But not all SIEMs deliver the same visibility, detection quality, or operational efficiency.

Microsoft Sentinel is often deployed as part of a broader Microsoft stack. It integrates tightly with Microsoft products, but onboarding complete telemetry from external sources can require tuning, normalization, filtering, or custom development.

New-Scale Fusion uses behavioral analytics, automated timelines, and embedded AI agents to improve detection quality and reduce manual effort. It analyzes cloud, on-premises, and third-party telemetry without requiring migration to a single ecosystem.

Here are five differences to consider as you evaluate which approach better fits your security operations.

1. Broader Ecosystem Visibility Without Vendor Constraints

Microsoft Sentinel integrates tightly with Microsoft products. Onboarding complete telemetry from external sources can require tuning, normalization, filtering or custom development, which can slow time to value in hybrid and multivendor environments.

New-Scale Fusion connects to nearly 700 products and includes more than 10,000 prebuilt parsers normalized through the Common Information Model (CIM). Teams can ingest cloud, on-premises and hybrid data without relying on proprietary query languages or Kusto Query Language expertise.

Outcome: You can onboard new data sources faster, apply consistent normalization and maintain broad visibility without ecosystem constraints.

2. Behavioral Analytics That Improves Detection Quality

Microsoft Sentinel includes user and entity behavior analytics (UEBA), but its native UEBA models are managed and cannot be rewritten. Customers can tune exposed parameters and build separate KQL or bring-your-own machine learning (BYO-ML) detections, but they cannot insert an arbitrary new source, behavioral feature or customer-defined algorithm into Microsoft native UEBA models. Exabeam lets customers author new learned behavioral analytics within the operational New-Scale Analytics engine.

Sentinel builds machine learning baselines from a defined set of UEBA-eligible sources. Within several sources, only selected event categories participate in the UEBA baseline. Unsupported vendor logs remain searchable, but they do not automatically become training observations in the managed UEBA baseline.

New-Scale Analytics applies behavioral analytics to data normalized through the CIM, so detections remain consistent regardless of telemetry source. MITRE ATT&CK mapping connects detections to known tactics, techniques and procedures (TTPs). Dynamic risk scoring identifies the behaviors analysts should investigate first.

Outcomes Navigator shows how detections align to ATT&CK and the OWASP Agentic Top 10, identifies use cases that need stronger coverage and helps teams determine where to improve. Automated timelines and integrated threat intelligence add context about why activity is significant and what to review next, without writing queries.

AI now operates as an execution layer in the enterprise. Securing AI requires more than platform monitoring, prompt filtering and static detections. Teams need to model behavior continuously and detect activity that deviates from expected patterns.

For agents created outside the Microsoft platform, Microsoft Defender coverage depends on more than registry enrollment in Agent 365 for centralized visibility. External agents must emit supported observability through SDK-level integration and operate through a covered tool or runtime path. Microsoft can discover some shadow agents, but visibility and enforcement are limited.

Microsoft guidance links long-term protection for agent identities to adoption of the Microsoft Agent ID framework. Sentinel detections act as an interim safeguard, while stronger protection depends on migrating agent identities into the Microsoft ecosystem. This creates an architectural dependency for organizations operating in cloud, SaaS and third-party platforms, where not all agents can be centralized in one identity system.

Agent Behavior Analytics (ABA) complements those controls by applying behavioral analytics directly to non-human identities. ABA models normal agent behavior automatically and detects subtle deviations in real time, including misuse and compromise that can appear legitimate in individual logs. You get consistent behavioral protection for Microsoft and third-party agents without migrating every agent identity or replacing your existing SIEM.

Outcome: You gain customer-authored learned analytics, risk-based prioritization, coverage guidance and continuous behavioral protection for users and AI agents.

3. Automated Timelines That Accelerate Investigations

With Microsoft Sentinel, analysts often correlate alerts, logs and context across tools. Security Copilot can assist, but it uses Security Compute Units (SCUs). Microsoft 365 E5 customers receive limited included capacity during 2026, while usage and workflow coverage still vary.

Search timelines reconstruct the sequence of events for users and entities in one view. Context enrichment, integrated threat intelligence and dynamic risk scoring explain what happened, when it happened and why it warrants attention. The workflow reduces manual correlation and query building.

Outcome: You can accelerate triage and investigation, reduce tool switching and improve mean time to detect (MTTD) and mean time to respond (MTTR).

4. Predictable Pricing and Built-In Compliance Resources

Microsoft Sentinel costs extend beyond data ingestion and can include queries, automation, integrations, storage and AI usage. License tiers and usage patterns can make total cost harder to forecast.

New-Scale Fusion uses a modular, transparent pricing model. Core behavioral analytics, automation and AI capabilities are included, while optional capabilities such as long-term storage can be added as needed.

Built-in dashboards and templates help teams report against frameworks such as PCI DSS, HIPAA and GDPR.

Explore Exabeam compliance capabilities.

Outcome: You can forecast total cost more predictably, avoid a usage-based fee for core Exabeam AI capabilities and accelerate compliance reporting.

5. Embedded AI Agents That Improve Security Operations

Microsoft delivers generative AI through Security Copilot. It operates under a separate SCU-based model, and its Sentinel integration remains limited to specific use cases such as incident summarization. Microsoft AI agents are also distributed among products, which can fragment the analyst experience and add licensing considerations.

Exabeam Nova AI is embedded in New-Scale Fusion. Seven coordinated agents address posture guidance, natural-language search, visualization, threat scoring, investigation, analyst assistance and rule creation.

Exabeam Nova Guided Investigations provides persistent, platform-wide assistance that collects context, accelerates search and triage and helps analysts move from investigation to response. Claude Enterprise ingestion expands visibility into sanctioned AI platforms by normalizing prompts, tool calls and actions into a timeline view.

Outcome: You can apply AI in daily workflows through one analyst experience for detection, investigation and response, without a separate usage-based fee for core Exabeam AI capabilities.

Conclusion

Choosing a SIEM requires more than comparing features. Detection quality, operational efficiency and cost all affect outcomes.

New-Scale Fusion connects behavioral models to dynamic risk, prioritized cases and complete timelines. This continuity helps teams detect subtle threats, accelerate investigations and strengthen an existing security stack without requiring platform replacement.

Download the full guide, Exabeam vs. Microsoft Sentinel: Five Ways to Compare and Evaluate, to explore the differences in more detail.