Arcanna

Arcanna accelerates and scales human decision-making in the SOC with trustworthy AI decision models—reducing noise, improving accuracy, and enabling agentic workflows.

We have several major Enterprises and MSSPs as customers, and we’re in ongoing pilots with several more. Some of the most noteworthy current customers are Accenture’s MXDR team (beginning global rollout) and IBM’s managed services function. In 2024 we were named to Gartner’s list of Cool Vendors for the Modern SOC.

In most Enterprise and MSSP SOCs, there are far more alerts than the analyst team can handle. Much of that work is tedious, repetitive, and ripe for automation, but the automation needs to understand the organization's context and evolve easily as things (the threat landscape, acceptable risks, internal policies) change. Similar problems exist in other core SOC functions such as Threat Hunting, Threat Intelligence filtering, and Incident Response.

Our CPU-based, bespoke Decision Models learn how a company’s SOC triages alerts and acts in other high-volume workflows requiring accuracy. Models embed directly into existing analyst workflows (i.e. SOAR playbooks and AI Assistants), grounding them with an evolving digital clone of the SOC’s expertise. Decisions come with a confidence score, outlier info, and details about why it decided what it did, equipping analysts (or other automation) with critical details to gauge how much to trust it. Our Models are a cost-effective, high-confidence filter to decide when agents should investigate.

We sell our platform as an on-prem or customer-owned cloud solution. The platform is priced based on the tiered number of Use Cases (i.e. Decision Models) a customer requests. The tiers are 5, 10, and 25 or more. Agentic Investigation functionality leverages customers’ LLM licenses and is currently included in the cost of our platform. Several customers on the top end pay more than $250k annually.

CrowdStrike/AWS Cybersecurity Accelerator, Wipro Enterprise Accelerator