Theseus Guard
The World's First Stateful AI Governance Platform
5 followers
The World's First Stateful AI Governance Platform
5 followers
Theseus Guard is a stateful AI governance platform built for the Agentic Internet. Unlike stateless guardrails that evaluate interactions in isolation, it tracks agent identity and behavior across multi-turn sessions, nested agents, and lifecycle changes. It combines real-time runtime enforcement, behavioral drift detection, and tamper-evident cryptographic provenance—so enterprises can govern autonomous AI continuously, enforce policies at inference time, and prove what happened.
Asking a frontier model to police its own hallucinations and security breaches is a fundamentally flawed security posture.
General-purpose models were trained to converse, assist, and generate code. They were never designed to be neutral, mathematically anchored constitutional adjudicators.
When enterprise agents touch production APIs, customer databases, and physical robotics, generic prompt wrappers and self-evaluating LLMs simply don't hold up.
Today, we are announcing TG-Sentinel:G1 — the world’s first unified foundation model family purpose-built exclusively for AI governance, technical risk analysis, and real-time runtime enforcement.
Rather than relying on brittle, slow, and expensive frontier model prompts, G1 decouples the governance plane from the task execution plane.
Key architectural & benchmark highlights:
⚡ 46B-A19B | 7+1 MoE Architecture: 1 shared expert holding factual constitutional & legal discipline, with 7 dynamically routed risk & domain experts.
⚡ Extreme Serving Efficiency: Sub-60ms Time-To-First-Token (TTFT) and 14,000+ generated tokens/sec on just 2× NVIDIA H100 GPUs (FP8 W8A8).
⚡ 100% Threat & Compliance Interception: Verified across 35 Cybersecurity vulnerability datasets (CVE, SSRF, SQLi, RBAC) and OWASP LLM Top 10 live probes.
⚡ 100% Deterministic JSON Schema: Zero syntax breaks across high-concurrency continuous batching stress tests.
⚡ Near-Zero Disruption: A calibrated 1.11% safe over-block (false positive) rate.
⚡ Embedded Taxonomies: Native alignment with the EU AI Act (Art. 14), NIST AI RMF, ISO 42001, OWASP, and defense-grade export controls.
A special thank you to NVIDIA, AWS, and Lambda for providing the critical infrastructure, compute, and engineering support that powered G1's training and evaluation.
Decoupling governance from generation isn't just an engineering preference—it is the prerequisite for enterprise AI autonomy.
Read the full technical breakdown, benchmarks, and official Model Card here: https://theseusguard.com/blog/introducing-tg-sentinel-g1
AI agents need more than content filters. They need runtime governance. 💪
We are proud to announce that Theseus Guard, Inc. has filed a U.S. provisional patent application (64/149,945) covering a stateful, tenant-specific governance architecture for AI agent executions. 🥳
Our approach is designed to resolve governance policies at decision time, selectively evaluate risk, authorize tools and external actions, enforce bounded outcomes, and preserve auditable provenance for every governed decision.
This milestone strengthens our intellectual property foundation as we work toward making enterprise AI more accountable, secure, and operationally trustworthy.
From AI experimentation to governed execution. The journey has begun. 🚀
We tested Theseus Guard Enterprise according to the OWASP Top 10 LLM 2026 document published 5 days ago. The initial results are as expected. ;) The LLM model you use with Theseus Guard doesn't matter. TG protects against even the most current risks.
Meet the Zero-Trust AI Data Plane:
For organizations using cloud or remote LLM APIs, Zero-Trust AI Data Plane prevents sensitive PII and/or proprietary company information from reaching external models while preserving the task-relevant context needed for high-quality responses.
More than a PII filter: Zero-Trust AI Data Plane is a policy-aware runtime mediation layer that governs AI interactions before they reach external LLMs, protecting sensitive data while preserving the context required for useful model responses.
Secure AI communication without sacrificing usefulness!