AI Code, Enterprise-Ready

Stop Risky AI

Your rules. Real-time guardrails. Trusted code—AI or human

One unified layer of governance—from enterprise SaaS platforms to modern AI-driven dev tools

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ASSURANCE

Vibe Code. Verified.

Our Model Context Protocol Server injects your organisational rules into the context window of any AI code assistant (e.g. Copilot, ChatGPT), before code is generated.

  • Enforces your rules in real time inside VS Code

  • Shapes LLM output using structured compliance context

  • Guarantees secure, consistent, and compliant code — before PR

CUSTOM POLICIES

LIVE ENFORCEMENT

REGULATORY COMPLIANCE

SERVICENOW, SALESFORCE, ADOBE & MORE

ASSURANCE

AI Prompt Assurance

Audit how prompts are designed, stored, and governed across any GenAI stack — with policy checks built for enterprise environments.Works with LangChain, custom APIs, NOW Assist, Agentforce, etc.

  • Listens to GitHub repositories and pipelines.

  • Applies tone, context, and structure checks with clause mapping (EU AI Act, ISO 42001, NIST).

TONE CHECKS

CONTEXT ACCURACY

REGULATORY COMPLIANCE

PIPELINE SECURITY

SALESFORCE

Salesforce Agent Readiness

Evaluate how ready your Salesforce environment is to deploy agentic AI with confidence — including Agentforce and GenAI-based workflows.

  • Evaluates org readiness for deploying agents in Salesforce using the MCP.

  • Checks metadata exposure, plugin activation, data tagging, access roles, and semantic indexing.

  • Highlights misconfigurations that would break agent trust chains or generate hallucinations.

AI Readiness Scanner

Metadata Scan

Security Review

Speed Test

Data Tasks

Pluggin Status

AI Readiness Scanner

Metadata Scan

Security Review

Speed Test

Data Tasks

Pluggin Status

AI Readiness Scanner

Metadata Scan

Security Review

Speed Test

Data Tasks

Pluggin Status

SERVICENOW

NOW Assist Validator

Assess how prepared your ServiceNow instance is to safely adopt NOW Assist and GenAI-powered features.

  • Security posture — scripting risks, protocol usage, plugin configurations

  • Data exposure — detection of sensitive or unstructured content in prompts, KBs, or virtual agent flows

  • Platform readiness — ensure required plugins, roles, and indexed content are in place

  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





SERVICENOW

NOW Assist Validator

Assess how prepared your ServiceNow instance is to safely adopt NOW Assist and GenAI-powered features.

  • Security posture — scripting risks, protocol usage, plugin configurations

  • Data exposure — detection of sensitive or unstructured content in prompts, KBs, or virtual agent flows

  • Platform readiness — ensure required plugins, roles, and indexed content are in place

  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





  • import requests
    # Hypothetical API endpoint for Quality Clouds metrics
    API_URL = "https://api.qualityclouds.com"
    API_KEY = "your_api_key_here"
    headers = "Real_Time_Code_Analysis"
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
    response = requests.get(API_URL, headers=headers)
    if response.status_code == 200:
    data = response.json()
    issues = data.get('issues_found')
    recommended_actions = data.get('recommended_actions')
    print(f"Issues Found: {issues}")
    print("Recommended Actions:")
    for action in recommended_actions:
    print(f" - {action}")





Trusted by engineering leaders at:

Trusted by engineering leaders at:

Trusted by engineering leaders at:

AI Readiness

Measure how prepared your platforms are to safely adopt AI — before a single model goes live.

Quality Clouds assess the technical foundation of your ServiceNow and Salesforce environments to ensure they’re ready for Agents

AI Readiness KPI

Quantifies how prepared your platform is to safely adopt AI — scoring data quality, plugin setup, and infrastructure configuration in one metric.

Data & Feature Checks

Verifies data models, security settings and other parameters related to AI implementation, with fix recomendations

Operational Gaps

Detecs missing roles, poor-quality knowledge content and ACL conflicts

AI Readiness KPI

Quantifies how prepared your platform is to safely adopt AI — scoring data quality, plugin setup, and infrastructure configuration in one metric.

Data & Feature Checks

Verifies data models, security settings and other parameters related to AI implementation, with fix recomendations

Operational Gaps

Detecs missing roles, poor-quality knowledge content and ACL conflicts

AI Readiness KPI

Quantifies how prepared your platform is to safely adopt AI — scoring data quality, plugin setup, and infrastructure configuration in one metric.

Data & Feature Checks

Verifies data models, security settings and other parameters related to AI implementation, with fix recomendations

Operational Gaps

Detecs missing roles, poor-quality knowledge content and ACL conflicts

What can I help with?

Discover and govern shadow AI while ensuring compliance and explainability. Just give me a command

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Add document

Analyze

Monitor

Report

What can I help with?

Discover and govern shadow AI while ensuring compliance and explainability. Just give me a command

|

Add document

Analyze

Monitor

Report

Dev Task in Progress..

Unit Tests

Code Review

Deployment

Queued

Pending

Compleated

Dev Task in Progress..

Unit Tests

Code Review

Deployment

Queued

Pending

Compleated

AI Orchestration & Operations

Gain control over GenAI in production — ensuring safety, compliance, and transparency at every step

From pilots to production, we make sure your AI agents are traceable, compliant, and aligned to internal policies and global standards.

Prompt & Agent Oversight

Audit prompts and AI logic for structure, safety, and compliance.

Standards Alignment

Verify adherence to EU AI Act, ISO 42001, and NIST RMF.

Shadow AI Detection

Surface and control untracked or unsanctioned AI activity across platforms.

Prompt & Agent Oversight

Audit prompts and AI logic for structure, safety, and compliance.

Standards Alignment

Verify adherence to EU AI Act, ISO 42001, and NIST RMF.

Shadow AI Detection

Surface and control untracked or unsanctioned AI activity across platforms.

Build Apps on Solid Ground. Govern with Confidence.

Discover how our tools prepare your platforms and control your AI — before, during, and after deployment.

Only 1 percent of enterprises we surveyed view their gen AI strategies as mature. Call it the ‘Gen AI Paradox’. For all the energy, investment, and potential surrounding the technology, at-scale impact has yet to materialize for most organizations

McKinsey, Seizing the Agentic AI Advantage, June 2025

Your Biggest Challenges, Answered

How organizations use Quality Clouds eliminate AI risk

Our AI prompts live in multiple tools—how do we control them?

We need to comply with ISO 42001 and EU AI Act, but don’t know how

Our teams build fast—we can’t slow them down with audits.

Our AI prompts live in multiple tools—how do we control them?

We need to comply with ISO 42001 and EU AI Act, but don’t know how

Our teams build fast—we can’t slow them down with audits.

Stop Hoping Your AI is Compliant — Start Verifying It

With QC AI Shield, you move from blind deployment to traceable, auditable AI control.

For Developers

Receive real-time feedback code safety.

For AI Consultants

Get visibility across all GenAI use.

For Governance Leads

Verify alignment to EU AI Act and ISO.

For Developers

Receive real-time feedback code safety.

For AI Consultants

Get visibility across all GenAI use.

For Governance Leads

Verify alignment to EU AI Act and ISO.

For Developers

Receive real-time feedback code safety.

For AI Consultants

Get visibility across all GenAI use.

For Governance Leads

Verify alignment to EU AI Act and ISO.

Explore our Products

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