Bring Your AI Workflows and Automation On-Premises with Trellix Wise and HyperAutomation 

Systems generate millions of security events and granular policy evaluations daily. Processing these volumes manually is statistically and economically unsustainable, especially when combined with sub-second response requirements and the chronic cybersecurity staffing shortages impacting public sector entities. To satisfy federal directives without overextending personnel, agencies require an automated infrastructure capable of operating at machine speed.  

Trellix addresses these structural challenges through a dual-layered architectural solution: Trellix Wise™ and Trellix Hyperautomation. Together, these platforms function as an integrated ecosystem designed to unify disparate security stacks, automate continuous policy enforcement, and operationalize zero trust principles within highly secure, air-gapped, and distributed on-premises federal networks.  

Part I: Trellix Wise On-Premises – The Federated Intelligence Layer 

Confronting the Low- and Medium-Severity Threat Visibility Gap 

In modern cybersecurity, federal agencies face a widening visibility gap between initial threat detection and definitive remediation. Organizations possess massive detection capabilities across fragmented vendor environments but limited ability to triage and remediate all of these detections. In between lies a vast volume of “medium” and “low” severity alerts where sophisticated, advanced persistent threat (APT) actors routinely hide and obscure their behavior. 

Historically, organizations have ignored an estimated 90% of security detections because human scaling has failed. Security Operations Centers (SOCs) simply cannot hire or train enough analysts to manually investigate the sheer volume of low- and mid-tier noise. As adversaries use automation to execute low-and-slow campaigns, ignoring this noise is no longer an option. This is exactly where threat actors establish their beachheads, moving laterally while remaining just under the threshold of high-severity alarms. 

Agentic AI Architecture: Moving Beyond the “Bolt-On Chatbot” 

To bridge this operational gap, many enterprise tools have rushed to deploy basic, generative AI “chatbots” bolted onto the side of an existing product interface. These passive assistants require a human analyst to manually copy and paste data, type out localized prompts, and wait for a static textual summary. A chatbot does not understand context, cannot execute secondary logic, and still leaves the entire analytical burden on the human operator. 

Trellix Wise On-Premises represents a fundamental paradigm shift from static generative AI to Agentic AI. Rather than acting as a passive chatbot, Trellix Wise is an autonomous, goal-oriented engineering infrastructure. It doesn’t wait for a prompt; it triggers automatically upon alert generation, executing complex multi-step logical playbooks to establish absolute context. Trellix Wise “shows its work,” providing a fully transparent, verifiable audit trail and evidence log behind every analytical decision it reaches, allowing human defenders to maintain complete situational oversight. 

Pure Stack Integration and the Federated Engine 

A foundational differentiator of Trellix Wise is its architectural positioning: it is a universal, vendor-agnostic infrastructure designed to work within your existing environment. Unlike traditional analytics platforms, it does not require a costly, high-risk “rip and replace” of your security stack, nor does it require massive data engineering to ingest data into a new centralized cloud repository. 

Trellix Wise operates on a federated data query architecture. It functions as a centralized intelligence layer that executes real-time, native queries across disparate security data storage bounds where they live. By leveraging over a decade of AI/ML modeling and nearly 25 years of specialized analytics experience, Trellix Wise comes directly to the customer’s data, offering an average of three more third-party integrations than competing solutions. The engine establishes direct connectivity to: 

• SIEM and Analytics Environments: Trellix Helix, Splunk Enterprise / Splunk Cloud, OpenSearch, and Elasticsearch data lakes. 

• Core Telemetry Engines: Network inspection appliances, identity providers, EDR solutions, and global threat intelligence feeds. 

By querying data natively within its original repository, Trellix Wise eliminates data transit and exfiltration risks, minimizes cloud storage overhead, and maintains strict adherence to data sovereignty boundaries. 

Level 3 Dynamic Investigation and Remediation 

When an alert fires Trellix Wise initiates an autonomous, Level 3 dynamic investigation. The engine mimics the reasoning patterns of an advanced tier-3 strategic threat hunter by asking and answering recursive contextual questions across the integrated stack: 

• What did the endpoint observe immediately before and after this event? 

• Are there concurrent or subsequent firewall or authentication rules firing for this specific device or user?  

• Is this administrative tool or executable typical for this user baseline, or does it match known adversary TTP actor sequencing? 

By cross-correlating what occurred, who was impacted, and historical baseline behaviors across multiple vendors, Trellix Wise builds a multi-vendor confidence matrix. Once the combined evidence reaches an actionable threshold of certainty, the platform issues a high-fidelity verdict (e.g., True Positive vs. False Positive). Rather than leaving a long list of half-analyzed alerts on a dashboard, Trellix Wise automatically coordinates with downstream security controls to safely remediate the threat, closing the exploit loop before human analysts even review the ticket. 

On-Premises Architecture for Air-Gapped Environments 

For highly regulated federal sectors, national security agencies, and critical infrastructure operators, standard cloud-based large language models (LLMs) present an unacceptable compromise to data sovereignty and physical security. Trellix Wise On-Premises is engineered explicitly for total physical isolation, running entirely inside air-gapped environments with absolutely no external network connections or cloud dependency.  

• Self-Hosted Large Language Models (vLLM): The platform features a fully self-hosted vLLM engine running localized, hardened models optimized specifically for advanced security intelligence and cyber threat analysis.  

• GPU Hardware Optimization: The inference engine is fully optimized for high-speed local performance using dedicated on-premises hardware, including NVIDIA H100 and H200 GPU accelerators.  

• Microservices Orchestration: Deployed completely within local enterprise Kubernetes clusters, such as Rancher Government Kubernetes Engine (RKE2) or Red Hat OpenShift, guaranteeing elastic local scaling, high availability, and structural resilience.  

• Computational Efficiency: To maximize on-premises hardware utilization and minimize redundant computation costs, Trellix Wise leverages an integrated LMCache layer across localized CPU and disk storage bounds.  

• Federal Compliance Hardening: The entire on-premises platform is hardened utilizing RapidFort software to ensure compliance with Federal Information Processing Standards (FIPS 140-3) cryptographic benchmarks and Defense Information Systems Agency (DISA) Security Technical Implementation Guides (STIGs) requirements.  

Part II: Trellix Hyperautomation – The Engine of Execution 

While Trellix Wise provides the analytical “thinking” engine to determine verdicts with absolute confidence, federal compliance mandates require an equally capable “doing” platform to execute responses at machine speed across the enterprise. This is the role of Trellix Hyperautomation—a comprehensive, low-code/no-code orchestration fabric designed to rapidly build, manage, and execute automated workflows across all organizational environments.  

Seven Industry-First Capabilities for Federal Zero Trust Compliance 

While traditional Security Orchestration, Automation, and Response (SOAR) tools can check some of the boxes for a Zero Trust Architecture, they often are prone to fail in federal deployment scenarios due to high setup costs, rigid script-based architectures, point-to-point integration fragility, and a structural inability to function without active cloud components. Trellix Hyperautomation introduces seven distinct architectural capabilities engineered explicitly to meet federal zero trust requirements:  

1. Distributed Edge Automation & Data Sovereignty: Lightweight, self-contained automated “Data Edges” run locally inside individual cloud regions or on-premises air-gapped networks. Data is processed exclusively at the collection point, removing the requirement to aggregate or transfer data to a backend data lake.  

2. Application-Agnostic No-Code Workflows: Rather than writing hardcoded playbooks restricted to specific vendors, creators utilize generalized actions (e.g., block_ip or isolate_asset). This loose coupling ensures playbooks remain resilient and allows agencies to exchange underlying security tools via a single click without rewriting orchestration logic.  

3. Federated Search & Actions: Representing an industry first, operators can initiate an on-demand or automated search for specialized artifacts (such as files, hashes, user accounts, or device identifiers) across more than 200 connected applications simultaneously from a single user interface.  

4. Multi-Instance Applications (Manager of Managers): Large federal organizations routinely run multiple separate installations of the same security appliance or tool across geographically separate networks. Trellix Hyperautomation configures all separate installations concurrently under a single application spec, executing automated playbooks or searching across all instances in parallel.  

5. Managed Mode Centralized Console: Provides enterprise-wide governance, central risk mapping, and multi-tenant playbook distribution. Administrators can standardize a single security playbook at headquarter level and securely push it across thousands of independently deployed local edge instances.  

6. Ease of Declarative Integration: Replaces manual script writing with open, spec-driven declarative integrations based on the Open Cybersecurity Framework (OCSF). This architecture enables rapid onboarding and allows teams to construct secure custom triggers and APIs in minutes without writing code.  

7. Search Operator for Deep Threat Eradication: Integrates raw threat hunting directly into automated playbooks. If an endpoint platform flags malicious activity, the playbook can utilize the search operator to scan all local databases, email servers, and network files to identify, contain, and completely eradicate secondary infection vectors in one coordinated action.  

Measurable ROI Inside the SOC 

For every 100 alerts autonomously triaged and contextualized by Trellix Wise, a SOC recovers an average of 8 hours of manual labor. This allows junior personnel to instantly operate with the proficiency of tier-3 experts, significantly lowers Mean Time to Resolution (MTTR) from days to minutes, and systematically eradicates the hidden low- and medium-severity threats that adversaries exploit. Paired with the distributed execution power of Trellix Hyperautomation, federal enterprises can confidently defend their critical missions at machine speed.