Ensure humans remain meaningfully in control — with live oversight, defensible audit trails, and runtime intervention.
For AI, platform, and risk teams deploying autonomous agents in regulated environments.
AI systems are no longer just tools. They act, decide, and adapt — often without direct human supervision. That creates new risks.
Complex reasoning chains that are opaque to operators and stakeholders
No comprehensive records of what agents did, why, or who authorized it
Problems only surface after actions execute and harm is done
Governance must operate in real time.
MeaningStack sits alongside your AI systems to provide continuous oversight, control, and accountability — without slowing development.
See what autonomous systems are doing as decisions are made — not after incidents occur.
Immutable records of system behavior, decisions, and human authorization — ready for regulators, auditors, and incident reviews.
Human judgment embedded directly into autonomous workflows, with explicit escalation and approval paths.
Pause, override, or constrain systems before failures propagate or policies are violated.
Built to support EU AI Act requirements and emerging global AI governance standards.
Model-agnostic infrastructure that adapts to your stack
Always-on governance that runs alongside your systems
Governance becomes part of how the system runs from day one
Governance becomes part of how the system runs — not something you scramble to assemble later.
Provide verifiable evidence that humans remain in control of critical decisions
Complete audit trails for stakeholders, auditors, and regulatory bodies
Identify problems before they become systemic failures
Intervene at the moment of decision, not after the damage is done
This isn't just compliance. It's operational safety at scale.
Why now: With regulations like the EU AI Act shifting expectations toward continuous oversight and traceability, organizations are being asked to prove control — not just claim it.
Most "AI governance" tools focus on documentation and after-the-fact review.
MeaningStack focuses on what actually matters.
Governance moves from static checklists to active control.
MeaningStack is built for organizations deploying autonomous or semi-autonomous AI systems where failure, opacity, or non-compliance is not an option.
MeaningStack is typically purchased by leaders accountable for AI risk and operational safety.
You don't need to run the system — you need to defend it.
You don't need another tool — you need infrastructure that doesn't break velocity.
MeaningStack is operated by the teams closest to AI behavior and system performance.
If no one is accountable for AI behavior in production, MeaningStack is premature.
Autonomous systems are already here. The question is whether humans remain meaningfully in control.
For GCs, CTOs, and AI leaders deploying autonomous systems
No slides. No generic sales pitch.