About Artemes AI
We built Artemes AI because we've been the ones getting paged at 3am — and we knew the tools were lying to us.
Our founders came from incident response, red teaming, and infrastructure security. We lived the alert fatigue. We couldn't trust the legacy scanners to tell us the truth about our environments. So we built the one we wish we'd had.
The problem we refused to accept.
We watched the industry rely on scanners built in the early 2000s, hastily re-skinned for the cloud era. We saw tools performing blind CVE matching with absolutely no environmental context, generating reports that took 72 hours to compile and were outdated before they even landed in our inboxes.
Most unforgivably, we saw highly paid security engineers spending 80% of their time triaging false positives, chasing ghosts instead of hunting actual threats. The tools designed to reduce risk had become the primary source of operational friction.
Why Artemes AI is only possible now.
We didn't build another scanner. We built a platform that leverages a unique convergence of technologies that simply didn't exist at enterprise scale five years ago.
Deep Telemetry at Scale
Matured into a production-grade telemetry layer capable of sub-millisecond queries without agent bloat.
Autonomous AI Analysis
Reached the capability threshold required for deterministic, zero-hallucination configuration analysis.
Enterprise Cloud Infrastructure
GCP provided the private VPC isolation and SOC 2-compliant backbone needed to handle extreme data velocity.
The Breaking Point
"The threat landscape accelerated to the point where 72-hour scan cycles became indefensible. If you aren't analyzing state continuously, you are implicitly accepting compromise."
How we build (Our Principles).
We are highly opinionated. These aren't generic platitudes; these are the strict technical constraints we impose on ourselves.
Signal over noise, always
We would rather show 0 findings than 100 false ones. If we cannot cryptographically or configurationally verify it, we don't report it.
Telemetry-anchored AI
Every AI inference must trace back to a specific system artifact. The OS data is the source of truth. AI interprets. It never invents.
Remediation is the product
A finding without an actionable fix is just anxiety delivered in JSON. We provide exact commands, not vague advice.
Zero trust in our own assumptions
We red-team our own models daily. We have a dedicated adversarial testing function whose sole job is to make our AI hallucinate.
Built by practitioners
Every feature ships only if someone on the engineering team can honestly say, 'I would have killed for this during an incident.'
The team behind the telemetry.

Alex Reyes
Former red team lead at a Fortune 500 financial services firm. Built and burned 7 years of SIEM dashboards that nobody trusted. Founded Artemes AI after a breach that a 500-page Nessus report had technically 'covered'.

Dr. Sarah Chen
PhD in distributed systems, ex-Google SRE. Led the team that built GCP's internal threat detection pipeline. The architect of the zero-hallucination AI framework at the core of Artemes AI.

Marcus Webb
12 years in offensive security, published researcher. Runs the adversarial testing function. If he can break it, bypass it, or trick it into a false positive, it doesn't ship.

Priya Nair
Former staff engineer at a major cloud security vendor. Built the high-performance telemetry integration layer that powers Artemes AI's sub-millisecond telemetry collection across global fleets.
Momentum
Backed By
Lightspeed, Sequoia Scouts, and strategic angels from CrowdStrike and Palo Alto Networks leadership.
The team at Artemes AI has built the scanner we've all been waiting for. This is what Nessus should have become.
We're hiring the best.
We are a small team deliberately. Every engineer owns production. If you want to build the future of autonomous security analysis without the bureaucracy, join us.
If you've been burned by your scanner before, we built Artemes AI for you.
Stop accepting false positives as the cost of doing business. Stop fearing you'll miss a real threat in the noise.