AI Safety

We believe frontier intelligence must be built with safety as the foundation — not bolted on after the fact. Our work spans formal verification of model behavior, alignment research that scales with capability, and deployment frameworks that ensure responsible use.

A world where every deployed AI system comes with mathematical guarantees about its behavior — not promises, but proofs.

99.7%

Behavioral Compliance

2.3B

Parameters Verified

Verification Methods

Post-Deploy Violations

Focus Areas

Formal Verification

Mathematical proofs of model behavior using abstract interpretation and compositional analysis at billion-parameter scale.

Alignment Research

Ensuring capability and intention stay coupled as systems scale — from reward modeling to constitutional methods.

Red-Teaming

Four-layer adversarial testing: automated probing, human-led creative testing, model-assisted attacks, and external researchers.

Responsible Deployment

Capability-tiered deployment gates, continuous monitoring, and the structural willingness to halt or retract.

Publications

2026-03-15

Formal Verification at Scale: Proving Alignment Before Deployment

How mathematical guarantees can replace trust when deploying frontier intelligence systems.

Webbeon Safety Team

2026-02-28

The Red Team Diaries: Breaking Our Own Models

Inside Webbeon's adversarial testing program — how we stress-test frontier systems before they ship.

Webbeon Safety Team

2026-02-10

Responsible Scaling: When to Ship and When to Stop

A framework for making deployment decisions when capability outpaces understanding.

Webbeon Research