96%
of investigations resolved autonomously at Cursor
95%+
reduction in false positives at Canoe Intelligence
25 to 35%
of what Artemis surfaces is a multi-stage, multi-domain attack, against 1 to 2% in a traditional SIEM
Is Artemis an AI SOC?
Yes, and more. Artemis investigates and triages every alert the way AI SOC tools do. It also writes and tunes the detectors, works from raw events and a model of your environment, and acts on its conclusions, so it catches activity your existing tools never flagged.
Do I need a new set of agents for each SOC role?
No. Artemis is one system that runs detection, investigation, hunting, and response on the same data and the same model of your environment. There is no roster of agents to configure or pay for separately.
How is this different from a copilot in my SIEM?
A copilot helps an analyst write a query faster. Artemis runs the whole investigation and returns a judgement with its evidence, and the query behind every answer is there to check.
Do we have to send you all our data?
No. Send the sources worth storing and query the rest where it lives, in your SIEM, EDR, or data lake. Detection, search, and investigation work across both.
Do you train on our data, and where does it live?
No. Your data is not used to train models, and LLM calls run through Amazon Bedrock. Each customer runs in a dedicated, single-tenant cloud account, with in-region hosting available and data encrypted at rest.
What happens when Artemis is wrong?
Set your own verdict and give a reason. Your verdict stands over Artemis's judgement, and the reason becomes case memory that later investigations of similar cases follow.
Can we bring our own detection logic?
Yes. Import Sigma or rules from your current SIEM, write detectors in plain English or SQL, or manage them as code in your Git repository. Imported rules are translated by what they detect, so field names that differ between schemas are handled.