AI agent governance
Autonomous AI systems act, decide, and transact on behalf of the organizations that deploy them. Governing that autonomy is the defining oversight challenge of enterprise AI.
Aletheia works with institutions, entrepreneurs, and investors to design the governance structures agentic systems require: clear boundaries on what agents may do, verifiable audit trails of what they did, and human judgment preserved at the points where it matters most.
What we design
Oversight architecture
Decision rights, escalation paths, and accountability structures that keep agentic systems answerable to the people responsible for them.
Autonomy boundaries
Technical and procedural limits on agent capability — scoped permissions, constrained tool access, and enforced human checkpoints.
Evaluation & assurance
Risk evaluations and adversarial testing that verify systems behave within their mandate before — and after — deployment.
Perspectives
Short pieces on the questions underneath agentic governance: integrity, authorization, epistemic risk, machine identity, memory, and the limits of human oversight at machine speed.
- 01What Is AI Integrity?
- 02Adversarial AI: Why Governance and Safety Must Converge
- 03Epistemic Risk in AI
- 04AI Governance Across the Architecture
- 05What Does AI Control Mean?
- 06Agentic Autonomy and Human Agency
- 07From Alignment to Authorization
- 08Capability Is Not Mandate
- 09The Epistemic Attack Surface
- 10Action Provenance: Knowing Why an AI Acted
- 11Reversibility as a Principle of Safe Autonomy
- 12Governance at Machine Speed
- 13Control Debt
- 14When Safe Components Create an Unsafe System
- 15AI Identity: Who Is Acting?
- 16Delegation Without Abdication
- 17Memory Is Governance
- 18Human Agency as a System Property