### [Mnemomv2](https://free.ilovefree.com/)

**Published:** 2026-06-20T04:36:00

**Author:** ilovefree

**Excerpt:** Freemium + From $0.01/month. Mnemomv2 provides a trust infrastructure for AI agents through cryptographic proof and real-time risk assessment, issuing a public Trust Rating (0-1000) for agent decisions. It targets developers deploying agents in regulated workflows.

As AI agents handle more critical decisions — from financial transactions to healthcare recommendations — verifying their behavior becomes essential. Mnemom provides **cryptographic trust scores (0-1000)**, **Ed25519-signed verdicts**, and **ZK-STARK proofs** for AI agent actions on Base L2, detecting threats like prompt injection, PII leakage, and supply-chain compromises. The platform is Apache 2.0 licensed and installs in under 5 minutes.

Learn more at [mnemom.ai](https://mnemom.ai/?utm_source=ilovefree&utm_medium=directory&utm_campaign=listing) — freemium pricing starts at $0.01/month per agent.

## Traditional AI Monitoring vs. Mnemom

| Capability | Traditional Observability (Langfuse, Datadog) | Mnemom |
| --- | --- | --- |
| Threat detection | Manual rule setup, no cryptographic proof | Built-in detection: prompt injection, PII leakage, CEO fraud, supply-chain attacks |
| Trust scoring | No standardized scoring | Cryptographic trust rating (0-1000), bond-rated AAA-CCC, public on Base L2 |
| Audit trail | Logs stored in database, tamper-editable | Ed25519-signed verdicts, hash-chained, Merkle-anchored, append-only audit chain |
| Cross-tenant defense | Per-tenant isolation only | AEGIS network shares signed threat intel across all customers in under 30 seconds |
| Compliance | Manual report generation | EU AI Act Article 50 SDK preset, SOC 2 Type II readiness, ISO 42001 mapping |

The core distinction: traditional tools observe AI behavior, while Mnemom provides cryptographic proof of it. Every agent decision is signed, chain-linked, and exportable as an audit bundle for regulators.

## The Five-Layer Stack

Mnemom runs a five-layer architecture built around "cards" — signed, versioned declarations that govern agent behavior:

1.  **Alignment Cards** declare what an agent is intended to do, its autonomy limits, and audit requirements. The Agent Alignment Protocol (AAP) verifies decisions post-hoc against these declarations.
2.  **Protection Cards** define permissible inbound and outbound message perimeters — what data gets in, what gets out. Think of this as a firewall policy for each agent.
3.  **Agent Integrity Protocol (AIP)** checks every thinking block mid-turn, catching drift or manipulation during the reasoning process itself, not just at the output stage.
4.  **Safe House** screens messages for threats including prompt injection, indirect tool injection, and social engineering before they reach the agent.
5.  **AEGIS Protection Network** is the cross-tenant defensive layer. When one customer’s substrate fingerprint shows behavioral deviation, every customer on that substrate is auto-flagged and a signed Managed Rule propagates across all gateways within 30 seconds.

### Supply-Chain Detection

Mnemom stamps every evaluation with a substrate fingerprint — provider, model, SDK version, and optional lockfile hash. This catches supply-chain attacks that bypass package-level provenance verification. The platform specifically references the **Mini Shai-Hulud worm of May 2026**, which compromised 170+ npm packages including Mistral AI’s SDK suite with valid SLSA-3 attestations. AEGIS attributes anomalies across customers running the same substrate and propagates defensive rules before the next agent is hit.

## Compliance and Regulation

| Framework | Status | What Mnemom Provides |
| --- | --- | --- |
| EU AI Act Article 50 | SDK preset available (enforcement Aug 2, 2026) | Transparency disclosures, logging, machine-readable content marking |
| SOC 2 Type II | Readiness program in flight | Controls aligned with AEGIS pipeline and audit chain |
| ISO 42001 | Controls mapped | AI management system mapped to alignment-card lifecycle |
| HIPAA | Readiness | Healthcare agent compliance support |
| GDPR | Readiness | Data handling aligned with EU requirements |

### Where It Struggles

-   **Early-stage product** — AEGIS propagation targets (sub-30s P95) are measured goals, not yet guaranteed; first measurements planned 30 days post-GA
-   **Base L2 dependency** — the trust rating and audit trail rely on Base L2 blockchain; organizations uncomfortable with on-chain infrastructure may find this a barrier
-   **No direct reasoning analysis** — Mnemom monitors the execution surface and decision outputs, not the internal reasoning process of AI models
-   **Niche use case** — designed for organizations running AI agents in regulated industries; not relevant for simple chatbot or content-generation deployments
-   **Opaque pricing** — the $0.01/month starting price is likely per-agent; total cost for fleets of agents hasn’t been clearly published

**Visit [Mnemomv2](https://mnemom.ai/?utm_source=ilovefree&utm_medium=directory&utm_campaign=listing)** — https://mnemom.ai/

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