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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsCybersecurity company Torq announced a $140 million Series D financing in January 2026 at a company-stated post-money valuation of $1.2 billion. The round, led by Merlin Ventures, makes Torq a cybersecurity unicorn and brings its reported cumulative funding to $332 million. Torq says it will use the capital to expand its AI security-operations platform, accelerate product development and pursue U.S. federal and public-sector customers.
The deal at a glance
| Item | Reported detail |
|---|---|
| Financing | Series D |
| Amount | $140 million |
| Valuation | $1.2 billion post-money, as stated by Torq |
| Total funding | $332 million, according to the company |
| Lead investor | Merlin Ventures |
| Participating existing investors | Evolution Equity Partners, Notable Capital, Bessemer Venture Partners, Insight Partners and Greenfield Partners |
Torq’s exact-headline news page is dated January 14, 2026, while its detailed financing material refers to January 12. Bloomberg previewed the transaction on January 11 and SecurityWeek reported it on January 12. The unambiguous point is that the Series D was announced in January 2026. Torq’s financing announcement is available at torq.io/news/torq-seriesD; secondary reports appeared in SecurityWeek and Bloomberg.
The announcement does not disclose each investor’s contribution, the percentage of the company sold, dilution, liquidation preferences or other detailed terms. The $1.2 billion figure is a transaction valuation, not evidence by itself of revenue, profitability, market share or product superiority.
What Torq sells
Founded in 2020 by Ofer Smadari, Leonid Belkind and Eldad Livni, Torq markets an AI security-operations-center platform. Smadari is the company’s chief executive. The software is designed to connect to an enterprise’s existing security stack and automate work such as alert triage, enrichment, investigation, case management, response and remediation.
The Tool Desk
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How the AI SOC model works
Torq uses “AI agents” to describe software that can interpret a security task, gather context from connected systems, choose or execute a multistep workflow and return evidence to analysts. That is broader than generating a narrative summary. The company combines those agents with deterministic hyperautomation workflows, so some actions can follow explicitly defined rules while others handle more ambiguous investigations.
Torq says its platform offers 300 pre-built integrations and more than 4,000 pre-built steps. Those are vendor-reported product figures, not an independent benchmark. The integrations are intended to span security, cloud, identity, collaboration and threat-intelligence systems. Product information is published at torq.io/ai-soc-platform.
Rank #2
Why the financing matters
Security teams routinely face more alerts and investigation work than their analysts can handle manually. Torq’s investment thesis is that software can perform repetitive first-line tasks while people retain responsibility for ambiguous, high-impact incidents. Investor interest in this model reflects demand for automation as well as broader enthusiasm for AI-native cybersecurity products.
Merlin Ventures is strategically relevant to Torq’s stated expansion plan because the company is targeting U.S. federal and public-sector buyers. Continued participation by the prior syndicate also indicates that Torq’s existing backers supported the new financing. Neither point proves that Torq has won the market or that its technology outperforms alternatives.
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Torq says it protects hundreds of multinational enterprises and displays customer or customer-logo references including Marriott, PepsiCo, Procter & Gamble, Siemens, Uber, Virgin Atlantic, Valvoline and Wiz. Its corporate materials also claim 300% year-over-year growth, Fortune 500 adoption, millions of security tasks handled autonomously, up to a 90% reduction in investigation time for certain alert-investigation use cases and the ability to manage substantially more alerts without adding headcount.
These figures are company claims. The public announcement does not provide audited financial statements, a complete customer count, retention data, a methodology for the time-reduction figure or independent testing. Terms such as “first true AI SOC,” “100% triage” and “100X more alerts” should therefore be read as positioning language rather than established industry measurements.
Rank #4
Where the new capital is going
- Faster product innovation and development.
- Broader go-to-market operations and enterprise adoption.
- Expansion of the AI SOC platform in commercial markets.
- Entry into U.S. federal and public-sector markets.
- Work needed to address requirements such as the Federal Risk and Authorization Management Program, or FedRAMP.
Torq’s announcement describes FedRAMP and related controls as requirements it intends to navigate. It does not establish that Torq has completed FedRAMP authorization, secured a federal contract or achieved any particular government procurement milestone.
How Torq fits the security-software landscape
| Category | Typical role | How Torq positions itself |
|---|---|---|
| SOAR | Orchestrates tools through playbooks and repeatable workflows. | Adds AI agents and multistep reasoning to traditional automation. |
| SIEM | Collects, searches and correlates security data. | Uses SIEM and other systems as sources of context rather than replacing every data platform. |
| XDR | Detects and responds across endpoint, identity, cloud and related telemetry. | Acts as an automation and response layer across multiple vendors. |
| MDR | Provides monitoring and analyst services through an outside provider. | Sells software; it is not automatically a managed detection-and-response service. |
| AI SOC platform | Applies AI reasoning, security context and automation to SOC work. | Torq’s primary category and product positioning. |
The boundaries between these categories are not fixed industry definitions. Torq’s differentiator is its claim that AI agents and deterministic workflows can investigate and execute actions across an existing tool chain, rather than merely classify alerts or provide recommendations.
Best Value
Questions an enterprise buyer should ask
Automation and control
- Can the platform investigate, contain and remediate, or does it only triage?
- Which actions require approval, and can policies restrict destructive operations?
- Can analysts pause, override and roll back an action?
Accuracy and auditability
- What are the measured false-positive and false-negative rates?
- Does each conclusion show its evidence, data sources and workflow steps?
- How does the system signal uncertainty or missing context?
Integration and deployment
- Are the organization’s SIEM, endpoint, identity, cloud, ticketing and threat-intelligence tools supported?
- Are connectors read-only, action-enabled or both, and how are API changes handled?
- What are the cloud, hybrid, data-residency, tenant-isolation and customer-managed-runner options?
Security, compliance and economics
- What is Torq’s current FedRAMP status and what assurance reports are available?
- How are encryption, key management, retention, deletion and model-provider data processing handled?
- Is pricing based on users, alerts, workflows, executions, agents, data volume or an enterprise license?
- What minimum contract, professional-services and overage costs apply?
Risks behind the AI-SOC pitch
Greater autonomy can lower analyst workload but magnify the consequences of a mistaken action. Buyers should test whether malicious content in an email, ticket or threat feed could influence an agent, whether API permissions are narrower than necessary and whether poor telemetry undermines an investigation. They should also distinguish a fully autonomous action from an automated recommendation that still requires approval.
Consolidating many tools into one platform may reduce switching costs while creating a new central dependency and potential vendor lock-in. AI agents can handle ambiguous cases more flexibly than fixed playbooks, but deterministic workflows are generally easier to test and audit. Any performance claim should be evaluated against the buyer’s own data quality, integrations and approval processes.
What remains unknown
- Revenue, annual recurring revenue, margins and profitability.
- Customer retention, expansion and the exact number of paying customers.
- The financing structure, dilution and valuation methodology.
- Public pricing, contract minimums and implementation costs.
- Independent tests of accuracy, safety or investigation-time improvements.
- Torq’s current FedRAMP position and any federal contract awards.
- The proportion of actions performed autonomously versus approved by humans.
Bottom line
Torq’s $140 million Series D is a substantial financing and places a company-stated $1.2 billion valuation on investor expectations for AI-driven security operations. The strategic opportunity is clear: reduce repetitive SOC work across a complex enterprise tool chain and pursue government customers. The investment should not be mistaken for proof of profitability, market leadership, FedRAMP authorization or superior AI accuracy. Those judgments depend on measurable adoption, retention, economics and safeguards for high-impact actions.
Quick Recap
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