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Texas AGI Labs
Pioneering Safe Artificial General Intelligence Research

Built-In Safety for Real-World AGI Deployment

Safety at Texas AGI Labs is not a post-hoc filter. It is embedded into objectives, training signals, architecture, and runtime control.

Our systems are designed to operate under constraints, expose uncertainty, and provide hooks for human and automated oversight, even under adversarial or high-pressure conditions.

Reliability

Multi-layer evaluation, regression gates, and continuous monitoring before and after deployment for critical behaviors.

Transparency

Structured logging, interpretable control surfaces, and enforced explanation channels for high-impact decisions.

Containment

Domain, tool, and action constraints by default, with hardened sandbox environments and rapid rollback paths.

Operational Safety Model

Every deployment follows a staged pipeline modeled on aerospace and launch operations.

  1. Adversarial simulation across red-team and synthetic scenarios.
  2. Constrained rollout with strict monitoring and abort conditions.
  3. Continuous policy updates based on real-world feedback signals.
  4. Guaranteed intervention hooks for shutdown and behavior overrides.
[Placeholder: Safety architecture diagram — control stack, monitors, and override channels.]

Safety Programs & Partnerships

We collaborate with external reviewers, domain experts, and institutional partners to stress-test systems in realistic conditions. Security, misuse resistance, and policy alignment are integral to every engagement.

Work With Our Safety Team

To discuss audits, evaluations, or formal partnerships, reach out through the contact channel referenced on the homepage. Selected partners gain access to deeper technical documentation and reports.