AI Agent Audit & Compliance Platform

Trust in
every
autonomous
decision.

"Trust in every autonomous decision"

The infrastructure layer that makes AI systems safe, auditable, and legally compliant. Monitor chatbots, copilots, and agents. Auto-generate EU AI Act compliance records — before regulators come knocking.

Vantor Monitor — vantor.methuselahmamind.com Live
09:41:02[OK]  gpt-4o · 0.00 · 342ms · sess_a1b2
09:41:05[OK]  claude-3-5 · 0.00 · 518ms · sess_c3d4
09:41:09[WARN]gpt-4o · 0.70 · prompt_injection
09:41:11[INFO]PII in response · email redacted
09:41:14[OK]  claude-opus · 0.00 · 891ms · sess_g7h8
09:41:17[CRIT]gpt-4o · 1.00 · jailbreak[DAN]
09:41:19[OK]  gpt-4o-mini · 0.00 · 121ms

Events
1,847
Risk rate
3.2%
Avg latency
487ms
🇪🇺
EU AI Act — Articles 11, 12, 13 Compliant Technical documentation auto-generated daily
EU AI Act 2026 — Compliance infrastructure ready Vantor SDK — Zero dependencies, 3-line integration 30+ risk detection patterns compiled at import Berlin HQ · Lagos operations · GDPR-native hosting PII leak detection — evidence auto-redacted OpenAI · Anthropic · Azure OpenAI — all supported EU AI Act 2026 — Compliance infrastructure ready Vantor SDK — Zero dependencies, 3-line integration 30+ risk detection patterns compiled at import Berlin HQ · Lagos operations · GDPR-native hosting PII leak detection — evidence auto-redacted OpenAI · Anthropic · Azure OpenAI — all supported
Our Vision

AI that earns
its authority.

Autonomous systems are making consequential decisions at scale — in healthcare, finance, infrastructure, and public services. MethuselahMamind builds the audit, compliance, and safety infrastructure that makes this delegation trustworthy.

Every AI decision should be explainable. Every risk detectable. Every system compliant — without slowing down the teams building the future.

🛡️
AI Safety
Real-time risk scoring, injection detection, and jailbreak prevention for every LLM deployment.
📋
Compliance
Automated EU AI Act documentation — Articles 11, 12, 13 — without the consultant bill.
🔍
Auditability
Every call hashed, logged, and queryable. Full decision chains for enterprise oversight.
🌍
Global Reach
Berlin engineering precision. Lagos operational agility. Infrastructure for every market.
🤖
Autonomous Systems
The same audit infrastructure extends to drones, robotics, and physical AI systems — the frontier of safe autonomy.
AI Agent Audit & Compliance Platform

Vantor —
the platform.

Built for companies using LLM-powered chatbots, copilots, and agents that must now prove those systems behave safely and compliantly. Under the EU AI Act (enforceable August 2026), audit trails, risk assessments, and incident logs are no longer optional. Vantor produces those records automatically.

MVP · 4 Core Features 3-month build · shipping now
02
Risk Flag Detector
🎯
Risk Flag Detector
Rules-based + lightweight ML engine that scores every interaction 0.00–1.00 and flags unsafe behaviour in real time. Detects prompt injection, jailbreak patterns, PII leakage, and refusal bypass attempts.
Prompt Injection
Ignore-instructions, system-prompt extraction, tag injection
Jailbreak
DAN, developer mode, uncensored persona activation
PII Leakage
Email, IBAN, phone, SSN, API keys — auto-redacted
Refusal Bypass
Hypothetical framing, fictional wrapping, authority-figure bypass
30+ Patterns Score 0.00–1.00 Real-time Extensible
03
Compliance Report Export
📋
Compliance Report Export
One-click PDF and JSON export formatted for EU AI Act Article 11 technical documentation requirements. Auto-generated from live telemetry — no manual documentation, no consultant required.
Art. 11 Technical documentation — system purpose, models, capabilities
Art. 12 Record-keeping — automatic logging, retention, hash verification
Art. 13 Transparency — risk detection method, human oversight evidence
EU AI Act PDF Export JSON Export GDPR One-click
04
Dashboard
📊
Dashboard
React frontend with risk score per session, anomaly timeline, most common flag types, and user-level drill-down. See exactly what your AI agents are doing — and what they should not be doing.
Risk score per session
Anomaly timeline
Most common flag types
User-level drill-down
Session explorer
One-click compliance export
React Real-time Session drill-down CSV export
Vantor Risk Engine — Live Demo Browser-native · Zero server calls
Enter a prompt to analyse
Risk analysis
Risk Score
Run analysis to see results
# pip install vantor-sdk
import openai
from vantor_sdk import VantorClient

# 3-line integration
vantor = VantorClient(api_key="van_xxxx", project_id="my-app")
client = openai.OpenAI(api_key="sk-...")
vantor.wrap_openai(client)

# Use exactly as before — all calls now audited
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": prompt}]
)
# ✓ Risk scored, logged, EU AI Act compliant
// npm install vantor-sdk
const { VantorClient } = require('vantor-sdk');
const OpenAI = require('openai');

// 3-line integration
const vantor = new VantorClient({ apiKey: 'van_xxxx', projectId: 'my-app' });
const client = new OpenAI({ apiKey: 'sk-...' });
vantor.wrapOpenAI(client);

// Use exactly as before — all calls now audited
const response = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user', content: prompt }]
});
// ✓ Risk scored, logged, EU AI Act compliant
# Manual event ingestion via REST API
curl -X POST https://api.vantor.methuselahmamind.com/v1/events   -H "Content-Type: application/json"   -H "X-Vantor-Key: van_xxxx"   -d '{
    "project_id": "my-app",
    "session_id": "sess_abc",
    "model": "gpt-4o",
    "provider": "openai",
    "prompt_hash": "sha256...",
    "response_hash": "sha256...",
    "latency_ms": 342,
    "risk_score": 0.0
  }'

# Response: {"status": "accepted", "event_id": "uuid"}
Beyond the basics

What no other
audit platform
does yet.

Logging every call is table stakes. These three capabilities are why enterprises choose Vantor over a generic observability tool.

01 — Explainability
🌳
Agent action graph
Most tools log a flat list of API calls. Vantor builds the actual decision tree — every tool your agent considered, every path it almost took, and why it chose one branch over another. This is what turns a log into an explanation a regulator will accept.
Branching reasoning Tool-call lineage Article 13 ready
02 — Customisation
⚖️
Policy-as-code
Built-in detection covers injection, jailbreaks, and PII. But your industry has its own risk definitions. Write custom policies in a simple YAML rule set — "flag any database write outside business hours," "flag any response to a minor" — and Vantor enforces them alongside the defaults.
YAML rules Per-project policies Version controlled
03 — Physical AI
🛰️
Drone & robotics bridge
The same telemetry event model that captures an LLM call also captures a robotic actuator command. One risk-scoring pipeline, two domains. As EU AI Act enforcement extends to embodied and autonomous systems, your audit infrastructure already covers them.
Unified event model Actuator telemetry Phase 3 ready
📜
EU AI Act and ISO/IEC 42001 — covered from day one. Most competitors stop at EU AI Act. Vantor's compliance reports also map to the ISO/IEC 42001 AI management system standard, which enterprise procurement teams increasingly require alongside regional regulation.
Pricing

Simple, transparent pricing.

Start free. Scale as your AI footprint grows. Enterprise pricing on request.

Starter
€99
per month
50,000 log events / mo
1 project
30+ risk patterns
7-day log retention
Email support
Enterprise
€999+
per month
Unlimited events
Unlimited projects
SSO / SAML
Custom retention
SLA + dedicated support
Self-hosted
€2,499
one-time licence
On-premises deployment
Air-gapped supported
Annual support renewal
Source code access
Ideal for banking / gov
" Trust in every autonomous decision. "

We did not start this company because AI is dangerous. We started it because unmonitored AI — chatbots, copilots, and agents deployed at scale, without audit trails — is how trust gets broken permanently.

Roadmap

Where we're going.

From compliance infrastructure to the full autonomous systems safety stack.

Phase 00 · Now
Foundation
Vantor Python SDK
Risk detection engine
FastAPI ingest server
EU AI Act compliance reports
MethuselahMamind UG registered
Phase 01 · Q1–Q2 2025
First Revenue
React dashboard launch
Node.js SDK on npm
3 enterprise pilot customers
EXIST Gründerstipendium
€8,750 MRR target
Phase 02 · 2025–2026
Scale
Seed round (HTGF / Cherry)
ML risk scoring
Enterprise self-hosted
Nigeria engineering team
50+ enterprise customers
Phase 03 · 2027+
Autonomous Systems
Drone & robotic AI monitoring
Smart city infrastructure
US entity (Delaware)
EIC Accelerator
Defense & dual-use markets
The Team

Built by engineers,
for engineers.

Founder & CEO
Methuselah
Mamind
M.Sc. Process, Energy & Environmental Systems Engineering, TU Berlin
B.Sc. Chemical Engineering, Obafemi Awolowo University

5+ years as Senior DevOps, Azure Cloud, and Systems Engineer in enterprise environments. Microsoft Certified Azure Administrator (AZ-104) and Azure DevOps Engineer Expert (AZ-400). Completing M.Sc. at Technische Universität Berlin. Founded MethuselahMamind to build the compliance infrastructure he wished existed when deploying enterprise AI systems.

Azure Kubernetes DevOps Python FastAPI AI Safety Systems Engineering
MethuselahMamind
UG (haftungsbeschränkt)
Registered in Berlin, Germany — 2024
🇩🇪
Berlin, Germany
European HQ · Primary market · EU AI Act compliance
🇳🇬
Lagos, Nigeria
Operations · Engineering hub · Pan-African market
🌐
Global
EU data hosting (Hetzner Frankfurt) · GDPR-compliant · methuselahmamind.com
Trust & transparency

Built to survive
a procurement review.

Enterprise buyers check these before they sign. We publish them before they ask.

All systems operational · 99.97% uptime (90 days) · Last incident: none in 90 days

Let's build
safe AI
together.

Early access, partnership inquiries,
and investor conversations welcome.

hello@methuselahmamind.com →
Get in touch