Our philosophy
We don't build AI and then make it safe. We build AI that is safe by construction.
Most companies treat safety as a constraint — something that limits what their models can do. We treat it as a capability. A model that can't be manipulated is more useful than one that can. A system that explains its reasoning is more powerful than a black box. Safety doesn't slow us down. It's what makes our technology worth trusting.
How we build safe systems
- Interpretability first — Every model we ship must be explainable. We invest in mechanistic interpretability — understanding not just what our models do, but why. If we can't explain a model's behavior, it doesn't leave the lab.
- Adversarial by default — We assume every system will be attacked. Our models are trained against adversarial inputs from day one. We red-team continuously — not as a final check, but as a core part of the development process.
- Constrained at the architecture level — Safety constraints are not prompt instructions — they're embedded in the model architecture itself. Our models can't be jailbroken because the constraints aren't suggestions. They're structural.
- Open research, closed vulnerabilities — We publish our safety research openly. Attack vectors, defense mechanisms, evaluation benchmarks — the industry gets better when knowledge is shared. But we practice responsible disclosure: vulnerabilities are patched before they're published.
- Continuous evaluation — Safety isn't a one-time audit. Our models are continuously evaluated against evolving threat landscapes. We maintain adversarial benchmarks that grow harder over time — because attackers don't stand still.
How our models protect
Claeth — Autonomous cybersecurity AI that protects cloud infrastructure, scans code for vulnerabilities, and monitors endpoints in real time. Claeth doesn't follow rules — it understands threats.
- Real-time threat detection across cloud, server, and endpoint
- Autonomous vulnerability scanning in production code
- Zero-signature detection — identifies novel attack patterns
- Continuous learning from proprietary security datasets
Prion — Real-time defense against prompt injection, jailbreaks, and AI manipulation. Prion sits between the user and the model, analyzing every input before it reaches the system.
- Blocks prompt injection and jailbreak attempts in real time
- Zero-latency analysis — no perceptible delay to the user
- Adaptive defense that evolves with emerging attack techniques
- Works with any LLM — not just Neuraphic models
Responsible disclosure
If you discover a security vulnerability in any Neuraphic product, model, or infrastructure, we want to hear about it. We take every report seriously and commit to responding within 48 hours.
We will never take legal action against researchers who follow responsible disclosure practices. We believe security improves when researchers and companies work together.
Send your findings to disclosure@neuraphic.com with steps to reproduce. Include as much detail as possible.