The modern SOC is not short on data. It is short on attention. Analysts work through queues measured in tens of thousands of events per day, and the interesting ones — the targeted, the novel, the quiet — are buried under a steady hum of commodity noise. The result is familiar to anyone who has worked a night shift on a detection team: fatigue, missed signal, and a growing gap between what the tooling produces and what the humans can actually read.
Neuraphic was founded to close that gap, starting from a specific conviction: the AI systems deployed into security environments must themselves be secure. A triage model that can be jailbroken by a crafted log line is not a defense — it is a new attack surface. We build for teams who cannot accept that trade.
Why this matters now
Attackers have already adopted generative AI. Phishing kits write better copy than they did two years ago, malware authors automate evasion, and commodity intrusion tooling now includes prompt-injection payloads targeted at the defensive AI sitting inside SIEM and EDR pipelines. Defenders who deploy off-the-shelf language models into their detection stack are inheriting an unexamined attack surface at the exact moment it is being actively probed.
Meanwhile, the volume problem keeps getting worse. Cloud telemetry, identity logs, and application traces compound faster than headcount ever will. Security leaders are being asked to do more with AI precisely because the alternative — hiring the gap away — is no longer available.
"A triage model that can be jailbroken by a crafted log line is not a defense — it is a new attack surface."
Defending the model edge
Prion is our inference-time defense layer for language models. It classifies and neutralizes adversarial inputs — prompt injection, jailbreaks, data exfiltration attempts, tool-abuse patterns — before they reach the model that will make a decision on your behalf. Prion runs in front of any model you already operate, including your own fine-tunes, and its judgments are structural rather than heuristic: constraints are encoded into the processing graph, not added as a filter to be argued with.
Autonomous infrastructure triage
Claeth operates as an autonomous cybersecurity analyst. Designed to take the low-risk, high-volume end of the triage queue — deduplication, enrichment, first-pass disposition on well-understood alert classes — Claeth returns the analyst's attention to the work that actually needs a human. Claeth tests patches and automated responses against ephemeral shadow twins, and it operates under explicit capability bounds that cannot be overridden by user prompts.
Both systems are designed to be auditable. Every decision Claeth takes, and every block Prion raises, is logged with its reasoning in a form your detection engineers can review, replay, and contest.
We meet SOCs where they already operate. Prion runs in front of the model endpoints your team already uses, whether those are hosted or private. Claeth integrates through the same alert pipelines as a human analyst — reading from your queue, writing dispositions back, escalating what it cannot justify. Neither product requires you to centralize data with us, and neither requires your operators to learn a new console as the price of admission.
For teams with stricter isolation requirements, we support private deployment into customer-controlled infrastructure. Our canonical architecture keeps compute on your side of the boundary and does not require outbound calls to Neuraphic-hosted services for inference.
Compliance and trust
We are working toward formal security and privacy attestations and publish our posture openly as we go. Our Trust Center tracks what is in place today, what is in progress, and what we will not claim until it is audited. We prefer honest gaps to polished overstatement.
Our safety philosophy and Responsible Scaling Policy describe how we evaluate our own systems before we put them in front of yours. The same standards that govern what we deploy to customers govern what we deploy to ourselves.
Get started
If your team is evaluating AI for detection, triage, or response — or trying to figure out how to secure the AI it already runs — we would like to hear from you. Write to security@neuraphic.com for technical conversations, or enterprise@neuraphic.com to discuss a deployment.