Modulos vs Cranium AI: AI Governance Comparison (2026)

Modulos discovery reads the AI platforms a company has connected. On request, Scout pulls agents from Azure AI Foundry and deployments from Azure OpenAI, inventories Copilot Studio agents across a Microsoft tenant, and reads usage from the OpenAI Platform organisation and the Claude Console, where API-key use shows who is calling which model. Access is read-only, and each find stays a proposed Draft until a person confirms it. On submission, Modulos checks completeness, runs an initial risk assessment and routes the system to a Registration Manager, whose approval or rejection is recorded with a reason.

Cranium’s Discover module runs four sensors. CodeSensor scans source code for models, datasets and AI packages, CloudSensor watches cloud changes, AgentSensor maps agents and the tools they call, and Detect AI looks for shadow AI. Cranium says discovery is continuous. Each system gets an auto-generated AI bill of materials listing components, dependencies, lineage, owners and usage, and vendor AI sits in the same system of record. However, we found no published approval workflow for admitting a system to that record.

The Modulos edge: Each system enters the Modulos register through a human confirmation, a first risk assessment and a recorded approval, so the inventory doubles as audit evidence.

Agent Tests answer a compliance question on a timetable. A team writes the check in plain English and schedules it daily, weekly, monthly or quarterly. On each run, an agent gathers evidence from the connected systems through read-only tools and returns pass, fail or error with citations. Each run is stored immutably. A fail returns each mapped control to not executed and alerts its owner. An error leaves control state alone, and a pass on the next run does not restore a control by itself. Modulos does not attack models and offers no red-teaming.

Cranium’s Secure module attacks AI the way an adversary would. Cranium Arena runs agent-based attack suites automatically and continuously, simulating prompt injection, jailbreaks and data leakage drawn from MITRE ATLAS, OWASP and Cranium’s own threat libraries. Arena Shield then generates remediations, applies guardrails and re-tests to confirm that the fix held. A runtime layer blocks, redacts, flags or quarantines risky prompts, responses and agent actions by policy. Through a Weights & Biases partnership, security evaluations can also run as a native step in model development.

The Modulos edge: Conformity status in Modulos follows scheduled verdicts on your own systems, and Cranium’s red-team results can be filed against the same controls as evidence.

Modulos maps 26 frameworks in library release 1.1.0, among them the AI Act, GDPR, NIS2, DORA and the Cyber Resilience Act. On 14 October 2026 the Official Journal carried the reference of EN 18286 on quality management systems, the AI Act’s first harmonised standard. Organisations that apply it are presumed to conform with Article 17(1) and with the first sentence of Article 11(1). Two more standards, prEN 18228 on risk management and prEN 18282 on cybersecurity, sit in the library as drafts. A security team also finds the OWASP Top 10 lists for LLM and agentic applications in the same library as ISO/IEC 27001, ISO/IEC 42001 and NIST AI RMF. Where obligations overlap, controls are shared, and the EU AI Act and NIST AI RMF have 58 in common.

Cranium’s Govern module maps systems to NIST AI RMF, the EU AI Act and ISO 42001 out of the box, next to custom internal standards. Its ComplianceAgent automates framework completion under human oversight, and compliance is scored continuously per system and use case. Cranium also publishes an OWASP Top 10 mapping. However, we found no harmonised standard in Cranium’s published material, no mapping for the CRA, NIS2 or DORA, and no framework for Singapore or the Gulf states.

The Modulos edge: Security and regulatory frameworks share one control set in Modulos, so evidence gathered for one framework counts toward every other framework that uses the same control.

The Fermi Risk Agent gives each AI risk an annual loss figure in EUR, GBP or USD. Because scheduled jobs re-run it, a failed control or new evidence shows up in the next figure. In the portfolio view a CRO can drill from the whole organisation to one threat vector, coloured by the share of each Risk Limit in use. The AI System Graph follows a threat through its risk to the AI system it affects, in money, and every value keeps its history. Modulos is also a founding member of PACT AI, a coalition working on AI assurance and insurance.

According to its Observe page, Cranium monitors more than 100 AI-specific risk signals in real time, including PII, prompt injection, jailbreaks, leakage and toxicity, and classifies over 250 intents. Its verdicts are deterministic and explainable, with the samples and scores behind each decision on view. That gives a security team strong operational telemetry, but we found no monetary method for expressing AI risk as of 16 October 2026.

The Modulos edge: Each AI risk gets an annual loss figure tracked against Risk Limits, the unit a board and its insurers already work in.

Modulos collects evidence from the systems where AI is built and run, from the Claude Console and Copilot Studio to Snowflake, Langfuse and GitHub. Vijil, an integrated source, supplies trust scores and guardrail data. Findings from Zenity, an agent-security partner, can be attached as evidence. A change history on each AI system shows who edited its profile, owners, frameworks, risks and evidence, and when. Modulos itself has a SOC 2 Type 2 report and ISO/IEC 42001 product conformity certificate 213-001/24 from CertX. It runs as SaaS, with private cloud, on-premise and air-gapped deployment available on request.

Cranium’s Prove module turns posture, red-team results and runtime evidence into AI Cards, exportable transparency reports for each system that can be shared with customers, partners and regulators. Teams can also publish standards and evidence to private or industry-wide Trust Hubs. The Aiceberg acquisition on 21 May 2026 added agentic AI risk-mapping technology, and Aiceberg’s CEO Alex Schlager became Cranium’s CTO. Cranium’s website lists no certifications and does not describe deployment options, so ask for both during an evaluation.

The Modulos edge: Modulos brings the ISO/IEC 42001 product certificate and SOC 2 Type 2 report a procurement team checks, and Cranium’s AI Cards can be attached to Modulos controls as evidence.