◆ Limited Design Partner Program now open — 4 spots remaining Apply →

The data layer that makes AI agent deployments insurable

Defensible deployment for autonomous AI agents. Cryptographic proof of what agents did, verified against physical reality. Audit-ready from day one.

▸ View Documentation ◉ Live Simulator
System Status All systems operational
Test Coverage
120+
Attack Vectors Defended
20
TLA+ Properties Verified
5

Private Pilot Program

We're onboarding teams who need defensible agent deployments.

The Problem
2026-01-05 09:14:32 [AGENT-7x9f] Authorized: purchase_supplies
2026-01-05 09:14:33 [AGENT-7x9f] Executed: $2,847.00 → vendor_id_unknown
2026-01-05 09:14:34 [AUDIT] DISCREPANCY: No vendor verification record
2026-01-05 09:14:34 [LEGAL] LIABILITY: Unattributable transaction
2026-01-05 09:14:35 >

Without mdash, you're shipping liability. Every agent action is a potential audit failure.

The Signal

Already, 80 percent of organizations say they have encountered risky behaviors from AI agents, including improper data exposure and access to systems without authorization.

— McKinsey, October 2025

Autonomous AI agents require clear permission boundaries, audit trails, and accountability mechanisms that most organizations have yet to construct.

— Lumenova AI, State of AI 2025

How It Works
Step 01
Authorize
Every agent action requires explicit warrant authorization with bounded parameters.
Step 02
Execute
Agent operates within defined constraints, all actions logged to immutable trace.
Step 03
Attest
Cryptographic seal verifies outcome against physical reality. Audit-ready.
Four Pillars
◈
Warrant System
Every agent action requires explicit authorization with bounded parameters. No implicit permissions.
◉
Physics Engine
Validate agent claims against physical reality. Impossible outcomes are rejected automatically.
◎
Checkpoint Surety
Rollback insurance for high-stakes operations. Every checkpoint is a safe recovery point.
◇
Sealed Context
Cryptographic proof of decision context. Tamper-proof records for every authorization.
◆ Limited Program

Design Partner Program

Shape the future of AI agent liability infrastructure

We're selecting 10 enterprise teams to co-develop mdash's governance primitives. Design partners get direct access to the core team, priority feature development, and preferred commercial terms at GA.

Ideal Partners

  • Deploying autonomous AI agents in production
  • Navigating compliance requirements (SOC2, HIPAA, financial regs)
  • Need audit trails for agent actions
  • Willing to provide feedback on early builds
◈

Direct Access

Weekly syncs with core team

◉

Priority Roadmap

Your use cases shape direction

◎

Preferred Terms

Locked-in pricing at GA

◇

Early Access

6+ months before GA

4 spots remaining for Q1 2026 cohort

Validation
120+
Tests Passing
20
Attack Vectors Defended
5
TLA+ Properties Verified

Last verified: 2026-01-17 12:00:00 UTC

“Permission is not proof.”

mdash provides governance without control.

We don't prevent agents from acting. We ensure every action is attributable, bounded, and recoverable. The question isn't "should this agent act?" It's "can we prove what this agent did?"

Get Started
For Engineers
  • Full SDK documentation
  • Integration guides
  • API reference
  • Example implementations
View Docs →
For Executives
  • Executive briefing
  • Compliance roadmap
  • Risk assessment framework
  • Insurance partnership info
Request Briefing →
◆ Limited
Design Partners
  • Direct access to core team
  • Priority feature development
  • Preferred commercial terms
  • 6+ months early access