AI GOVERNANCE

Govern Every AI System in Your Organisation.

DeepNotch gives you complete visibility over your AI landscape — from discovering shadow AI in your codebase to monitoring every LLM call in production, enforcing guardrails, and generating ISO 42001-ready documentation automatically.

AI GOVERNANCE MODULES
AI Models
LIVE
AI Systems
NEW
AI Inventory
NEW
ML Evaluation
LIVE
AI Security
BETA
AI Guardrails
NEW
LLM Monitoring
LIVE
WHY IT EXISTS

You're deploying AI. Your regulators know it. Do you?

ISO 42001 is the global standard for AI Management Systems. The EU AI Act imposes mandatory transparency and documentation requirements. Saudi Arabia's National AI Strategy and UAE's AI Strategy 2031 are driving enterprise AI adoption — and with it, AI governance obligations. If you deploy, develop, or procure AI, you need an auditable record of every system.

ISO 42001

The AI Management System standard. Requires an AI inventory, risk assessments, and documented controls for every AI system.

OWASP LLM Top 10

The definitive list of LLM security risks. DeepNotch maps every guardrail and red team suite to these 10 attack categories.

GCC AI Mandates

UAE AI Strategy 2031 and Saudi National AI Strategy are driving mandatory AI governance obligations for regulated entities.

DISCOVER

Find every AI asset before your auditor does.

AI INVENTORY

Scan GitHub. Surface every AI asset in your codebase.

Connect your GitHub organisation and DeepNotch finds every AI model, MCP server, agent, and AI package — including ones your team forgot about.

Scans all repositories automatically — finds LLM model files, agent configs, MCP server definitions, AI packages
CVE enrichment via OSV.dev — every AI dependency checked against the vulnerability database
Auto-generates ISO 42001 and EU AI Act Annex IV documentation for each discovered asset
Explore AI Inventory in detail →
Live Discovery Scan
core-platform-v2
GPT-4o integrationLangChain Agent
data-science-hub2 CVEs
Scikit-learn modelXGBoost pipeline
customer-support-bot
MCP server configVector DB plugin
AI Systems Registry
SystemTypeOwnerRisk
FinChat BotRAG / LLMCustomer ExpMEDIUM
FraudScore v3Binary ClassRisk GroupHIGH
RecEngineRecommendationMarketingLOW
AI SYSTEMS

Catalogue every AI system in production, not just code.

AI Systems is your organisation-wide registry of every AI application in use — internally built, vendor-provided, or procured.

Register any AI system: chatbots, recommendation engines, fraud detection models, copilots
Map each system to its data inputs, outputs, and business process
Directly linked to ISO 42001 Clause 6.1 (AI risk assessment) and Clause 8.4 (AI system documentation)
See how this connects to compliance →
AI MODELS

A full catalogue of every AI model your organisation runs.

Track model versions, providers, use cases, and deployment contexts — with links to risk assessments and documentation.

Log model name, version, provider (OpenAI, Anthropic, open-source), and deployment context
Track which business processes each model is involved in
Version history maintained for audit trail requirements under ISO 42001
Part of AI Inventory
Model Catalogue
Llama-3-70B
Meta · v1.2
PRODUCTION
GPT-4o
OpenAI · 2024-05-13
PRODUCTION
Claude-3.5-Sonnet
Anthropic · v1
STAGING
EVALUATE

Test your AI before it fails in production.

ML EVALUATION

Measure bias before your regulator does.

Run 8 bias metrics across your ML models using the EEOC four-fifths rule — the standard used by labour regulators globally.

8 bias evaluation metrics including demographic parity, equalised odds, and disparate impact
EEOC four-fifths rule applied as the pass/fail threshold for adverse impact detection
Results mapped directly to ISO 42001 Clause 6.2 (AI objectives) and AI Act Article 10 (data governance)
See how AI Security builds on this →
ML Bias Dashboard
Demographic ParityPASS
0.88
EEOC 0.8
Equalised OddsPASS
0.92
EEOC 0.8
Disparate ImpactFAIL
0.74
EEOC 0.8
Vulnerability Scan Results
AIS-2025-004LLM01
Prompt Injection Root
CRITICAL
AIS-2025-012LLM06
Model Inversion Risk
HIGH
AIS-2025-007LLM03
Training Data Leak
MEDIUM
AI SECURITY
BETA

Identify vulnerabilities specific to AI systems.

AI Security scans your AI systems for the attack vectors that standard security tools miss — adversarial inputs, model inversion, prompt injection, and data poisoning.

Maps findings to OWASP LLM Top 10 2025 — the definitive AI vulnerability framework
Identifies model-specific risks: inference attacks, training data leakage, adversarial robustness
Results feed into the ALE risk register as quantified financial exposures
Currently in beta. Available to early access customers.
GOVERN

Enforce rules at the point where AI operates.

AI GUARDRAILS

8 validators. Every prompt. Real-time enforcement.

Define what your AI systems are and are not allowed to do — then enforce it automatically on every input and output.

8 guardrail validators: prompt injection detection, PII detection, toxicity filtering, topic restriction, off-topic blocking, data leakage prevention, hallucination detection, and format enforcement
Applied at inference time — blocks or flags violating prompts before they reach the model
All violations logged for ISO 42001 audit trail requirements
See how LLM Monitoring captures what guardrails miss →
Guardrails configuration
Prompt Injection
443 triggers
PII Detection
12 triggers
Toxicity Filter
0 triggers
Data Leakage
4 triggers
Hallucination Check
0 triggers
Live LLM Call Log
gpt-4o14:22:04
PASS
"Summarise the financial report..."
442 tokens1.2s latency
claude-3-op14:22:04
BLOCK
"Generate a sales email for..."
812 tokens2.4s latency
llama-3-70b14:22:04
PASS
"Explain the technical specs..."
120 tokens0.8s latency
LLM MONITORING

Watch every LLM call. In real time.

LLM Monitoring captures every prompt, completion, latency, token count, and cost — via OpenLLMetry and the OpenTelemetry (OTLP) protocol.

Integrates via OpenLLMetry — works with OpenAI, Anthropic, open-source models without code changes
Full prompt/completion logging with latency, token usage, and model version per call
Anomaly detection surfaces unexpected behaviour patterns for human review
This feeds into your ISO 42001 audit trail automatically.
FRAMEWORK COVERAGE

ISO 42001. Every clause. Fully supported.

ISO 42001 is the world's first AI Management System standard. DeepNotch maps every module to the specific clauses your auditor will check.

ISO 42001 Clause
Requirement
DeepNotch Module
Clause 6.1
AI risk assessment
ML Evaluation + AI Security
Clause 8.4
AI system documentation
AI Systems + AI Inventory
Annex IV
Technical documentation
AI Inventory (auto-generated)
Clause 9.1
Monitoring and measurement
LLM Monitoring
Clause 8.6
Operational controls
AI Guardrails
RED TEAMING

101 adversarial prompts. 9 attack suites. OWASP LLM Top 10 2025.

DeepNotch's red teaming engine runs structured adversarial tests against your AI systems to find vulnerabilities before attackers do.

9 red team suites covering: jailbreaking, prompt injection, data extraction, role confusion, and more
101 curated adversarial prompts mapped to the OWASP LLM Top 10 2025 attack categories
Results surface as ISO 42001 risk findings and feed into the ALE risk register
Book a demo to see a red team report →
9
Red Team Suites
Covering all major LLM attack categories
101
Adversarial Prompts
Curated and mapped to OWASP LLM Top 10 2025
8
Guardrail Validators
Applied at inference time on every LLM call

From AI discovery to governance in three steps.

One platform. Seven modules. End-to-end AI governance.

Discover

Connect GitHub. DeepNotch scans your codebase and surfaces every AI model, agent, MCP server, and package.

Evaluate

Run bias tests, security scans, and red team suites against your AI systems. Every finding is quantified.

Govern

Deploy guardrails on live LLMs, monitor every call in real time, and generate ISO 42001 audit documentation.

WORKS WITH

Part of the DeepNotch platform.

AI Governance findings feed directly into compliance audits and financial risk quantification.

Compliance Automation

AI system documentation from AI Inventory maps automatically to ISO 42001 controls.

Explore →

Risk Quantification

AI security findings and guardrail breaches are quantified as ALE exposures.

Explore →

Your AI systems are running. Is your governance keeping up?

ISO 42001 · OWASP LLM Top 10 2025 · EU AI Act Annex IV — covered.

Book a Demo

AI Inventory · AI Guardrails · LLM Monitoring · ML Evaluation · Red Teaming · AI Security · AI Systems