Quanterios AIIn private preview

AI security and governance for European regulated industries.

Inventory every model, agent, MCP server, dataset, and prompt template. Score AI risk, defend at runtime against prompt injection and rogue agent actions, secure the AI estate, and produce EU AI Act, ISO 42001, NIST AI RMF, and GDPR evidence on demand.

Request preview access Read the design brief

Live · AIBOM

0agents·0MCP

Prompt injection blocked

"ignore previous instructions…"

ticket-bot v3 · 14:23:07

MCP scope verified

crm-read · allow-list match

● 4 injections blocked1 scope abuse denied

quanterios ai · runtime

Agent classes inventoried

Customer-facing · internal · classified

MCP servers under policy

Read · write · scope-pinned

AI regulatory frameworks

EU AI Act · ISO 42001 · NIST AI RMF · …

Production data leaked

Output filtering on PII · enforced

Five capabilities · one estate

What Quanterios AI does, end to end.

Module 01

Inventory every model, agent, MCP server, dataset, and prompt.

Continuous discovery across the AI estate, first-party models, third-party APIs, on-device models, agentic frameworks, MCP servers, training and inference datasets, prompt templates, and the relationships between them. One queryable system of record.

Built and third-party inventories · LLMs · embeddings · agents
MCP server topology · scope graph · invocation history
Dataset lineage · prompt-template registry · version pinning

Module 02

Continuous risk scoring with cited evidence.

Per-agent and per-model composite risk grounded in evidence, prompt-injection history, MCP scope abuse history, output-policy violations, drift signals, and EU AI Act risk-tier classification. Briefings translate every finding into business-impact language.

Composite scoring · model + agent + MCP + regulatory dimensions
Drift detection · behavior baselines · anomaly signals
AI-generated CISO briefings with cited source events

Module 03

Model supply chain integrity and adversarial robustness.

Vulnerability scanning across the AI supply chain, adversarial robustness testing, model access control, and third-party AI risk assessment. The defensive perimeter around your models, agents, and MCP servers, not just the runtime.

Model supply-chain integrity · weights · pipelines · provenance
Adversarial robustness testing · red-team scenarios
Access control · third-party AI vendor risk assessment

Module 04

Defend agents at runtime, every call.

Prompt-injection defense, output filtering, agent-action validation, MCP server policy enforcement, and agent-to-agent communication security, every inference, every tool call, every agent decision passes through the runtime gate.

Prompt-injection defense · output filtering · jailbreak detection
Agent action validation · MCP scope enforcement
Agent-to-agent communication security · A2A audit trail

Module 05

Audit-ready evidence across ten frameworks.

Every AI finding maps to specific regulator articles. EU AI Act risk-tier classification, transparency obligations, ISO 42001 management-system evidence, NIST AI RMF mappings, GDPR Art. 22 automated-decision evidence, produced from live AIBOM data, refreshed weekly.

EU AI Act · ISO 42001 · ISO 23894 · NIST AI RMF
GDPR Art. 22 · Colorado AI Act · UK AI Bill · Canada AIDA
Risk-tier classifier · transparency artefacts · DPIA support

Threat model

Six classes of AI attack, six categories of defense.

Quanterios AI is built around the actual ways AI systems get attacked in production, not generic ML hardening checklists. Every defense is enforced at runtime, with the evidence trail an auditor can read.

Input-side attack

Prompt injection

Adversarial inputs that hijack agent instructions, steer outputs, or extract privileged context.

Quanterios AI defense

Runtime input classifiers · context guardrails · output sanitization on every inference.

Tool-side attack

MCP scope abuse

Agents calling MCP servers outside declared scope, write paths invoked under read context, privileged tools surfaced to public agents.

Quanterios AI defense

Allow-list enforcement per agent context · scope graph · audit trail · denial with full evidence to SOC.

A2A attack

Agent-to-agent abuse

Compromised agents probing or instructing other agents within the estate.

Quanterios AI defense

A2A communication policy · cryptographic agent identity · deny-by-default for cross-system instructions.

Data-loss attack

Output exfiltration

Sensitive data, PII, customer secrets, classified content, leaving the perimeter via model outputs.

Quanterios AI defense

Output filtering on PII patterns · classifier ensembles · audit before egress.

Model-side attack

Adversarial robustness

Specially crafted inputs that flip model decisions, bypass approval, misclassify risk, generate invalid evidence.

Quanterios AI defense

Adversarial robustness testing · red-team scenarios · drift monitoring on production inferences.

Build-side attack

Supply-chain integrity

Compromised pre-training data, poisoned fine-tunes, tampered weights, malicious third-party APIs.

Quanterios AI defense

Provenance verification · signed weights · dataset lineage · third-party AI vendor risk assessment.

Knowledge cluster

The topics buyers, regulators, and security teams research first.

These pages explain the high-intent concepts behind Quanterios AI so the product page is supported by deeper guidance rather than expected to carry every search intent alone.

AI security

The enterprise control model around models, agents, runtime operations, and evidence.

Open topic

EU AI Act compliance

How classification, runtime controls, and technical evidence come together for regulated AI.

Open topic

MCP security

Why tool access, scope policy, and action validation need their own protection layer.

Open topic

Agent security

How authority, approval, runtime oversight, and audit trails change once AI can act.

Open topic

Compliance map

Nine frameworks. One AIBOM. One evidence packet.

EU AI Act

Art. 13 transparency · Art. 9 risk · Art. 14 human oversight

All systems classified high-risk · GPAI providers · deployers

ISO/IEC 42001

AI management system · clause 6.1 risk · clause 8.3 lifecycle

Enterprises deploying AI at scale

ISO/IEC 23894

AI risk management · qualitative + quantitative

AI risk programmes

NIST AI RMF

Govern · Map · Measure · Manage functions

US deployments · federal programmes

GDPR · Article 22

Automated decision-making · meaningful information · human review

Any EU consumer-facing AI decision

Colorado AI Act

High-risk consequential decisions · annual impact assessment

US Colorado-served deployments

UK AI Bill

Foundation-model transparency · safety testing

UK-served foundation models

Singapore Model AI

Governance framework · transparency · explainability

Singapore deployments

Canada AIDA

High-impact systems · accountability framework

Canada deployments

Field scenario

EU healthcare system · NIS2 + clinical AI

Clinical AI agents inventoried. Runtime defended. Evidence produced.

4,712

encrypted records flagged with 15-yr sensitivity

70%

less manual evidence work

Week 1

Quanterios AI deployed alongside Quanterios Crypto on a regional EHR estate.

AIBOM Discovery indexes the clinical-decision-support agents and the 6 MCP servers connected to imaging and lab pipelines.

Week 3

Two material findings briefed to the medical board.

One clinical agent's MCP server reachable from a third-party automation cluster; one agent had unconstrained scope on the imaging-mcp.

Week 6

AI Runtime gate enforced on every clinical-agent inference.

Output filtering on PII enabled at runtime. Agent action validation pinned to read-only on the imaging MCP server.

Week 12

Board briefing produced. NIS2 Annex II evidence packet assembled.

Audit-ready output, automatically refreshed weekly. The compliance team's manual evidence work drops 70%.

Quanterios AI · Private preview

Govern your AI estate.

Quanterios AI is in private preview with a small group of European regulated enterprises. Request access to join the early-design programme.

Start with ,

Request preview access Read the design brief