---
title: "AI Policy — MindLab"
description: "How MindLab designs, deploys and governs its AI systems: data use, human oversight, safety, transparency and customer controls."
url: "https://mind-lab.ai/ai-policy"
language: "en"
---

# Artificial Intelligence Policy

*March 28, 2026*

This Artificial Intelligence Policy ("AI Policy") defines how Mindlab AI LLC ("MindLab," "we," "us," or "our") designs, deploys, and governs artificial intelligence systems within its platform. The purpose of this policy is to ensure responsible and safe use of AI, define roles and responsibilities between MindLab and customers, mitigate operational, legal, and ethical risks, and establish governance standards aligned with enterprise requirements.

## 1. Purpose

This Artificial Intelligence Policy ("AI Policy") defines how Mindlab AI LLC ("MindLab," "we," "us," or "our") designs, deploys, and governs artificial intelligence systems within its platform. The purpose of this policy is to:

- Ensure responsible and safe use of AI
- Define roles and responsibilities between MindLab and customers
- Mitigate operational, legal, and ethical risks
- Establish governance standards aligned with enterprise requirements

## 2. Scope

This policy applies to all AI-powered components of the MindLab platform, including:

- Conversational agents (text, voice, avatars)
- Multi-agent orchestration systems
- Workflow automation and decision systems
- AI-generated outputs and recommendations
- Integrations with third-party systems (e.g., CRM, contact centers)

## 3. Definitions

- AI System: Any system that generates outputs (text, voice, actions) using machine learning or probabilistic models
- Output: Any response, recommendation, or action generated by the system
- Customer Configuration: Prompts, workflows, integrations, and knowledge bases defined by the customer
- High-Risk Use Case: Any use involving legal, financial, medical, or safety-critical decisions

## 4. AI System Characteristics

MindLab AI systems:

- Operate probabilistically (non-deterministic)
- Generate outputs based on patterns in data
- May vary in responses across similar inputs
- Can trigger actions through integrations

Important: AI outputs are not guaranteed to be accurate or complete.

## 5. AI Risk Classification Framework

Customers are responsible for classifying their use cases.

Low Risk:

- FAQ automation
- Basic customer support
- Product information

Medium Risk:

- Sales assistance
- Lead qualification
- Customer guidance

High Risk:

- Financial decisions
- Medical recommendations
- Legal guidance
- Identity verification

High-risk use cases require human oversight.

## 6. Human Oversight Requirements

Customers must implement human-in-the-loop controls when:

- Outputs impact financial, legal, or health outcomes
- Decisions affect customer rights or eligibility
- Errors could cause material harm

MindLab does not provide fully autonomous decision-making systems for high-risk scenarios.

## 7. Customer Responsibilities

Customers are responsible for:

- Designing and validating AI workflows
- Defining prompts and guardrails
- Ensuring data accuracy and completeness
- Monitoring outputs and system behavior
- Complying with applicable laws and regulations
- Implementing escalation to human agents

## 8. MindLab Responsibilities

MindLab is responsible for:

- Providing AI infrastructure and orchestration
- Maintaining system availability and performance
- Implementing baseline safeguards
- Enabling configuration tools for customers
- Monitoring platform-level performance

## 9. Data Governance

Data Ownership: Customers retain ownership of their data.

Data Processing: Data is processed solely to provide the Services.

Model Training:

- Customer data is not used to train shared models unless explicitly agreed
- Aggregated and anonymized data may be used for system improvement

## 10. Model and System Limitations

AI systems may:

- Generate incorrect or misleading outputs
- Reflect biases present in training data
- Misinterpret ambiguous inputs
- Fail in edge cases

Customers must not rely solely on AI outputs for critical decisions.

## 11. Safety and Control Mechanisms

MindLab implements:

- Prompt constraints
- System-level controls
- Monitoring and logging
- Rate limiting and abuse detection
- Access controls

Customers are responsible for implementing:

- Business logic constraints
- Validation layers
- Escalation workflows

## 12. Prohibited Use

The Services may not be used for:

- Illegal activities
- Fraud, impersonation, or deception
- Generating harmful or abusive content
- Violating privacy or data protection laws
- Fully autonomous high-risk decision-making without oversight

## 13. Third-Party Dependencies

MindLab may rely on third-party providers (e.g., LLMs, cloud infrastructure). We are not responsible for:

- Changes in third-party models
- External service outages
- Third-party data handling practices

## 14. Transparency and Disclosure

Customers should:

- Clearly disclose when users interact with AI
- Avoid misleading users into believing they are interacting with humans
- Provide escalation paths to human agents

## 15. Bias and Fairness

AI systems may reflect biases. MindLab:

- Continuously improves model performance
- Monitors system-level behavior

Customers are responsible for:

- Evaluating fairness in their use cases
- Avoiding discriminatory outcomes

## 16. Security

We implement:

- Encryption (where applicable)
- Access controls
- Monitoring and logging

Customers must:

- Secure their integrations
- Protect credentials and access

## 17. Audit and Monitoring

MindLab may:

- Monitor system performance
- Analyze usage patterns
- Detect misuse or abuse

Customers should:

- Regularly review AI outputs
- Monitor KPIs and anomalies

## 18. Incident Management

In case of incidents (e.g., harmful outputs, system misuse):

- Customers must notify MindLab
- MindLab may investigate and mitigate
- Access may be restricted if necessary

## 19. Compliance

Customers are responsible for ensuring compliance with:

- Data protection laws (GDPR, CCPA, etc.)
- Industry regulations (if applicable)
- Internal governance policies

MindLab does not guarantee regulatory compliance for specific use cases unless explicitly agreed.

## 20. Liability and Disclaimer

AI features are provided "as-is". MindLab is not liable for:

- Decisions made based on AI outputs
- Errors or omissions in generated content
- Business outcomes resulting from AI usage

## 21. Continuous Improvement

We continuously:

- Improve models and infrastructure
- Enhance safeguards
- Adapt to regulatory developments

## 22. Policy Updates

We may update this AI Policy periodically.

## 23. Contact

Mindlab AI LLC, 306 1/2 35th St., Newport Beach, CA 92663. Email: j@mind-lab.ai