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Mautic

Based exclusively on public evidence • 20 criteria (Privacy + AI)
Last review: 21 Feb 2026

E+
AITS IA

AI Trust Summary

AI Training
Possibly (generic mention of service improvement)
Data Retention
Not specified in documentation
Opt-out
Only generic controls (cookies, ads)
AIPrivacy
E+
BasePrivacy
C+
  • On AI: does not mention the use of artificial intelligence, which may generate distrust regarding the processing of user behavior data.
  • On Core Privacy: documents data processing purposes, ensuring clarity on how information is used.

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Attention Points in AI (3)

AI criteria that require attention. Buy the Premium Analysis to see all 3 criteria.

  • Mautic
  • Does not declare the use of artificial intelligence, which may generate insecurity regarding data processing.
  • Omission of ethical AI principles and anti-bias measures raises concerns about discrimination.
  • It is advisable to require contractual clauses addressing these aspects before contracting.

Use of artificial intelligence is not disclosed in policies

There is no mention of artificial intelligence or its functionalities, which may generate distrust regarding the use of user behavior data.

Ethical AI principles and anti-bias measures not documented

There is no mention of commitments to the ethical use of AI, which may lead to concerns about bias and discrimination in data processing.

Features using AI are not identified in the policy

The policy does not describe AI-powered functionalities, which may generate uncertainties about how user behavior data is used.

Source: vendor public documents

Compliances in AI (3)

AI criteria the company meets. Buy the Premium Analysis to see all 3 criteria.

  • Mautic
  • Purposes of user behavior data processing are clearly listed, ensuring transparency.
  • Identifies data recipients in detail, including employees and service providers.
  • These practices facilitate due diligence by demonstrating responsibility in data processing.

AI training opt-out control available

The policy mentions controls for cookie management, but does not offer a specific opt-out for the use of user behavior data in AI training.

Policy on data use for AI training clearly stated

The policy mentions the use of information to improve user experience, but in a generic way, without clarity on specific use for AI.

Contestation and human review of AI decisions available

Provides general support channels for questions and requests, but is not specific to contesting automated decisions.

Source: vendor public documents

Highlights in Privacy (3)

Most relevant criteria for this category. Buy the Premium Analysis to see all 3 criteria.

Sensitive data processing without additional documented safeguards

The policy mentions data collected from public channels, but does not address specific sensitive categories, which may generate insecurity.

Processing purposes clearly listed by data category

The policy connects categories of user behavior data and campaign interactions to their specific purposes, ensuring transparency.

Personal data recipients clearly identified in the policy

Clear identification of recipients of user behavior data and campaign interactions, ensuring responsibility in processing.

Source: vendor public documents

Critical Alerts

  • Princípios de IA ética e medidas anti-viés não documentados: Importante para garantir a responsabilidade no uso de dados de comportamento do usuário..
  • Tratamento de dados sensíveis sem salvaguardas adicionais documentadas: Importante para garantir a proteção de dados sensíveis no contexto de campanhas.

Conformance analysis (20)

Premium Feature
AITS Criterion 12
Compliant

Purposes of user behavior data processing clearly listed

Reference: ISO/IEC 27701 (7.3)

AITS Criterion 14
Compliant

Recipients of user behavior data clearly identified

Reference: ISO/IEC 27701 (7.3)

AITS Criterion 10
Compliant

Identity and contact of the data controller clearly informed

Reference: ISO/IEC 27701 (7.3)

Source: vendor public documents

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Mautic Marketing Automation: Privacy and Security Insights

Transparency in Data Processing

Mautic excels in its transparency regarding data processing practices. Users can find clear information on the purposes for which their behavioral data is treated. This is crucial for compliance with regulations like GDPR and LGPD, which emphasize the need for organizations to inform users about data usage. With an AITS Privacy Score of 56%, Mautic demonstrates a commitment to clarity, allowing users to make informed decisions about their data. This transparency fosters trust, as users can easily understand how their information is utilized and who has access to it.

Clear Identification of Data Controllers

Another strength of Mautic is its clear identification of data controllers. Users can easily find the identity and contact information of the data controller, which is essential for exercising their rights under privacy regulations. This feature not only enhances user confidence but also ensures that users know whom to contact for any inquiries or concerns regarding their data. By providing this information, Mautic aligns itself with best practices in data governance, further solidifying its position as a reliable marketing automation tool.

Lack of AI Transparency

Despite its strengths, Mautic has notable weaknesses, particularly regarding its lack of transparency about artificial intelligence usage. The absence of information on whether AI is employed in data processing raises concerns among users, especially given the increasing scrutiny on AI ethics and privacy. With an AITS AI Score of only 13%, users should be cautious, as this lack of clarity could lead to potential misuse of their data. To mitigate this risk, users should inquire directly with Mautic about any AI applications and how they impact data handling.

Unaddressed Ethical AI Principles

Additionally, Mautic does not document ethical AI principles or anti-bias measures. This omission is significant, as it leaves users in the dark about how their data might be influenced by AI algorithms. Without these safeguards, there is a risk of biased outcomes in marketing campaigns, which could affect user targeting and engagement. Users are advised to actively seek out information regarding Mautic's approach to ethical AI and consider implementing their own checks to ensure fairness in their marketing strategies.

Recommendations for User Settings

To enhance privacy and security while using Mautic, users should take proactive steps in their settings. First, review the data processing purposes listed in the platform and ensure they align with your organization's privacy policies. Enable features that allow users to opt-out of data tracking where possible. Additionally, consider implementing data minimization practices, collecting only the information necessary for your marketing efforts. Regular audits of your data practices can help maintain compliance with GDPR and LGPD requirements.

Exploring Alternatives and Precautions

Given the identified weaknesses, users may want to explore alternative marketing automation platforms that offer stronger AI governance and data protection measures. Look for tools that provide comprehensive documentation on AI usage and ethical guidelines. In the meantime, ensure that your organization has robust data protection policies in place, including regular training for staff on privacy best practices. By staying informed and proactive, users can effectively navigate the complexities of marketing automation while safeguarding their data.

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Source: vendor public documents

Analyzed Sources

Public documents used in the audit of Mautic:

Evidence, confirmations and contestations

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Scope & Limitations

TrustThis/AITS assessments are based exclusively on publicly available information, duly cited with date and URL, following the AITS methodology (privacy & AI transparency).

The content is indicative in nature, intended for screening and comparison, not replacing internal audits.

TrustThis/AITS does not perform invasive tests, does not access vendor technology environments and does not process customer personal data. Conclusions reflect only the vendor's public communication at the date of collection.

Source: vendor public documents