Roadblocks on the way to machine speed
With AI-driven attacks on the rise, SOCs need to operate at machine speed. But the move to fight AI with AI creates multiple challenges for your SOC.
Unpredictable pricing and the high cost of tokenomics
Consumption-based pricing can make an agentic SOC difficult to budget, govern, and scale. Costs based on token usage can rise unpredictably—often when you need AI most to help with an incident.
Limitations of public cloud models
Most agentic solutions are entirely dependent on public cloud for AI reasoning—making them a non-starter for on-premises or air-gapped environments and severely limiting their usefulness during a breach.
Lack of confidence that limits automation
Your SOC needs to trust an agentic AI solution to make the right decisions before granting it further autonomy. Without visibility into AI reasoning and an ability to tune responses, SOCs face a confidence gap that slows adoption and limits automation.
Lack of data sovereignty
Typical agentic solutions force you to centralize telemetry into their data lake, incurring extra costs, transformation challenges, and inserting uncertainty about where your data is going.
Human-led automation with Trellix
The Trellix solution to running your SOC at machine speed fosters collaboration between human SOC analysts and AI agents. The solution builds the confidence you need to automate through observability and full audit trails, response tuning, and a confidence scoring framework, so you stay in control and accelerate at your own pace.
Deploy AI on your terms
Deploy AI across on-premises, hybrid, or cloud infrastructure while maintaining 100% data sovereignty. Your sensitive data never needs to leave your environment.
Reduce the costs of AI adoption
Eliminate runaway token costs with a clear, single flat-fee subscription model for predictable costs, even in times of heavy usage.
Gain the confidence to automate
Trust the decisions your agents make with transparent, step-by-step reasoning and audit trails. Leverage response policies that ensure agents act responsibly.
Increase your SOC capacity
Reclaim hundreds of hours every week, triage 100% of alerts, uplevel your junior analysts and feel confident that your team can defend against AI-driven cyber threats.
Trellix and the agentic SOC
At Trellix, our solution for the agentic SOC is grounded in years of experience in employing AI, ML, and agentic AI.
Our agentic security solutions are built on over a decade of AI modeling and 25 years in analytics and machine learning
Our AI and agentic capabilities are built on a foundation of industry-leading threat intelligence and decades of incident response.
Trellix Wise is the logic engine of an agentic security fabric that has been delivering real-world results of 100% alert triage and scaling SOC capacity 6x since its introduction more than two years ago.
Trellix Wise for Private Cloud: The core of your agentic SOC
Trellix Wise for Private Cloud is the groundbreaking solution for the agentic SOC that offers:
Full data and AI sovereignty. Runs entirely on your hardware or in your VPC with no need to connect to the public cloud. You control everything for AI on your terms.
Full visibility into reasoning and decision making, so you can trust it to make the right decisions
A predictable flat-fee subscription license—not a metered consumption-based model—so you can avoid surprise token overages and reduce costs.
Did you know ...
Agentic security that fights AI with AI
00%
Proportion of Layer 3 and 4 DDoS attacks targeting financial services.[1]
00%
Percentage of data breaches that involve a third-party vendor.[2]
$0.00M
Average cost of a data breach in the financial sector.[3]
Frequently asked questions
Automation in the SOC depends on confidence and trust in the agentic system. An AI agent that cannot tell you how sure it is forces your analysts back into the very work you deployed AI to eliminate in the first place. If every verdict must be re-verified, the agent has added a step, not removed one. A "confidently wrong" AI system may state a conclusion without sharing the strength of its evidence. The resulting lack of trust in AI reasoning and decision making can prevent automation that helps the SOC operate at machine speed to defend against AI-driven attacks.
As part of the Trellix solution, Trellix Wise provides transparent verdicts, attaching a calibrated confidence level to every case and reasoning step, revealing sources, what data was present or missing, and how closely patterns match known threats. When data is absent, it records "No Reputation Available" rather than inventing a verdict to ensure its credibility. Your team can rate any verdict, override its conclusion, or flag a specific piece of evidence for administrative review. Once an admin approves that feedback, Trellix Wise applies it to every similar investigation that follows. This gives your team an immediate, defensible basis for action so no analyst ever has to guess how far to trust the machine.
- Scaling capacity: Trellix Wise operates as a force multiplier for your SOC, enabling you to scale capacity and accelerate to machine speed without linear hiring increases.
- Ending alert fatigue: Trellix Wise takes ownership of the repetitive triage that can lead to analyst burnout and attrition. Every alert is investigated, enriched, correlated, and given a verdict automatically so your team is no longer buried under a queue that never empties.
- Elevating the analyst: Trellix Wise does not replace your people. By absorbing the tactical grind, it frees humans to do the strategic, high-judgment work that machines can't, while accelerating how quickly junior analysts grow into senior ones.
The Trellix agentic AI solution leverages Trellix Wise, which puts a human governance layer between reasoning and execution. High impact actions run under Human in the Loop approval, SOC managers can designate specific action types as permanently requiring sign off, a persistent Abort control halts execution across every connected tool, and when Trellix Wise cannot resolve which system owns an asset it escalates the ambiguity to a person rather than guessing. The result is that even an imperfect verdict cannot autonomously trigger an irreversible response.
Trellix Wise engineers reliability into the scaffolding around the model, not just the model itself. LLMs don’t store facts the way a database does, they store statistical relationships between tokens and then predict the next most probable token. That means any answer generated purely from weights or prior summaries is, by design, an extrapolation from patterns rather than a check against ground truth. Trellix Wise ensures conclusions are grounded in retrieved evidence rather than generated from the model's memory or summations to counter this liability
Trellix Wise Active Context Learning captures analyst decisions as ground truth, but it never lets that memory decay into liability. No feedback enters the model until an administrator approves it through the Feedback Review Queue, role based permissions ensure junior input cannot accidentally misinform the agent, and a configurable time to live expiration forces the agent to unlearn stale operational rules automatically. A dedicated conflict resolution queue surfaces contradictory feedback for manager adjudication, so the knowledge base stays consistent as it grows.
For air-gapped and disconnected environments, Trellix Wise for Private Cloud hosts its intelligence cache and models locally, unlike cloud-dependent tools that lose detection efficacy or ship your telemetry offsite the moment connectivity is constrained.
Related resources
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