About AliasPath™
AI needs your context. It doesn't always need your data.
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Generative AI is changing how organisations work. Lawyers analyse contracts, insurers process claims, financial institutions evaluate risk, and enterprises increasingly rely on AI agents to perform complex tasks.
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But there is a fundamental problem.
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To do useful work, AI needs context. And that context frequently contains personal information, confidential business records, privileged communications and commercially sensitive data.
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Today, organisations often face an uncomfortable choice. Allow sensitive information to reach AI systems, or restrict what employees and agents can do with them.
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We built AliasPath because we believe there is a better way.
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AliasPath is an independent AI data protection and governance layer that transforms sensitive information into realistic, context-preserving alternatives before it reaches an AI model.
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The model receives the information it needs to perform the task without receiving the original protected values. When the response returns, AliasPath can restore the original information within the authorised environment.
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Protect the data. Preserve the work.
The missing layer in enterprise AI security
For decades, organisations have controlled access to information. Identity systems decide who can see data, encryption protects it in transit, and data loss prevention watches where it goes.
Generative AI introduces a different problem. An employee or AI agent may have every right to access information and still disclose more of it to an external model than the task requires. The access is authorised; the disclosure may not be necessary.
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Permission to access information is not the same as permission to disclose it.
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AliasPath™ works at what we call the semantic boundary: the point where information is prepared for an AI model. Rather than relying only on detection, warnings or blocking, it transforms protected information before it crosses that boundary.
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The result is less unnecessary exposure, without giving up the usefulness of AI.
How AliasPath™ works
1. Identify what needs protection
AliasPath™ examines information being prepared for an AI model and identifies configured categories of sensitive data. These can include personal identifiers, financial information, health information and other protected values.
Its detection capabilities cover 2,003 patterns across 61 countries, including support for multiple languages and writing systems.
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2. Replace sensitive values with meaningful alternatives
Rather than deleting information or replacing it with generic labels, AliasPath™ generates realistic, contextually appropriate aliases.
A person's name remains a plausible name. A company remains a plausible company. Relationships between entities can be maintained across the protected workflow.
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The objective is to preserve the structure and meaning of the task without disclosing the original values.
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3. Let AI perform the work
The protected information is passed to the supported AI model or application. The model can analyse, summarise, draft and reason using the transformed information.
Users retain access to the capabilities of their chosen AI systems, within the integration and deployment options supported by AliasPath™.
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4. Restore information where authorised
When the AI response returns, AliasPath™ can replace recognised aliases with their original values inside the authorised environment.
The user receives an intelligible result containing the information needed to complete the task. The original protected values need not have been disclosed to the external model.
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Pseudonymise. Process. Restore.
Products
AliasPath™ Agent
Protection for AI interactions and agent workflows. Agent controls sensitive information as it moves between users, applications and supported AI systems, so organisations can use AI on real business information without disclosing the underlying values.
AliasPath™ Desktop
Practical protection for individual professionals and smaller teams. Protect documents before they go to AI systems or third parties; aliases keep the material useful, and authorised restoration returns the originals when needed.
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AliasPath™ API
The protection engine for developers and platforms. Build contextual pseudonymisation and restoration into existing applications and automated workflows, rather than asking users to adopt a separate tool.
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Privacy Proof
Evidence of what happened to protected information. Request-level visibility of each transformation and restoration, so organisations can show how sensitive information was handled.
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AI Risk Assessment
Find where sensitive information enters your AI workflows. We identify the most important exposures, review existing controls and prioritise where protection will matter first.
What makes AliasPath different?
We believe AI security should enable work, not simply restrict it.
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Many AI security platforms concentrate on discovering AI usage, detecting sensitive information, enforcing policies and blocking potentially unsafe interactions. Those controls remain important.
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But detection alone does not answer a fundamental question:
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Can the task still be completed without exposing the original information?
AliasPath™ approaches that question through contextual data transformation.
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Context matters
Removing names, identifiers and other protected information can make documents less useful to an AI model.
AliasPath™ substitutes realistic values intended to preserve the relationships, structure and meaning of the original material. This allows organisations to protect sensitive information without automatically sacrificing the context needed for useful AI outputs.
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Protection should follow the workflow
Employees should not have to choose between productivity and protecting confidential information.
AliasPath™ is designed to operate within supported AI workflows, applications and integrations, reducing the need for disruptive changes to how people work.
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AI security must extend beyond the prompt
As organisations move towards AI agents, the challenge becomes more complex. Agents can retrieve information, interact with applications, invoke tools and initiate actions. Protecting the initial prompt is only part of the problem.
AliasPath's broader direction is to provide enforceable controls over sensitive information as it moves through AI-enabled workflows, including what can be disclosed and where protected values may be restored.
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Security needs evidence
A security policy describes what should happen. Operational evidence helps demonstrate what actually happened.
AliasPath™ combines data transformation with visibility into protected interactions, supporting organisations that need to explain and review their AI data handling practices.
Built for organisations that work with sensitive information
AliasPath™ is particularly relevant where confidentiality, privacy and data protection are essential to everyday operations.
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Legal and professional services
Protect client information, privileged material, matter documents and confidential commercial records when using AI for research, analysis and drafting.
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Financial services and insurance
Reduce unnecessary disclosure of customer, policyholder and commercially sensitive information in AI-supported workflows.
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Regulated enterprises
Enable wider AI adoption while applying consistent controls to sensitive information across supported applications and models.
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Government and public sector
Support AI-enabled services and internal operations where information handling, jurisdictional requirements and accountability are critical.
Technology providers and MSPs
Embed contextual data protection directly into products, platforms and managed AI services through the AliasPath™ API.
Built by people who understand the problem
AliasPath™ was founded by Rob Westmacott and Darren Wray, who previously worked together building data protection and governance technology.
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Their experience spans enterprise software, privacy, regulated industries and the practical difficulties organisations face when introducing new technologies. They have seen how frequently security controls become barriers to productive work, and how readily users find ways around them.
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Generative AI makes that tension more significant. The objective behind AliasPath™ is straightforward: build protection that enables organisations to use AI productively while maintaining control over the information they disclose.
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Rob Westmacott
Co-founder
Rob has spent more than 25 years working with enterprises, law firms and regulated organisations on information management, data protection and governance. His background includes senior commercial leadership roles at Merrill Corporation and DFIN, alongside founding and scaling enterprise technology businesses.
He previously co-founded Guardum, a data protection technology company acquired in 2021. Rob leads AliasPath's commercial strategy, partnerships and international development. LinkedIn
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Darren Wray
Co-founder and CTO
Darren leads the architecture, engineering and development of AliasPath™. His background includes senior technology roles in regulated enterprises, including insurance, and extensive experience developing data protection and governance solutions.
He previously co-founded Guardum with Rob and led its technology development through to acquisition. Darren's focus is building security controls that work within real enterprise environments rather than imposing unnecessary complexity on users. LinkedIn
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Paul Hartzell
SVP Sales and Business Development, Americas
Paul is based in Denver, Colorado, and supports AliasPath's commercial development across the Americas, working with prospective customers, strategic partners and distribution channels. LinkedIn
How we work
We believe enterprise AI security should be practical, measurable and proportionate to the risk. That means starting from the actual information involved, the task being performed and the consequences of disclosure, rather than from a generic policy.
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Every engagement begins with a 30-minute technical demonstration with a member of the founding team. We then scope the workflows, models and data categories that matter, agree what a successful pilot looks like, and test the controls against real work. Customers deal with the people who built the product, from first conversation through deployment.
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AliasPath™ is developed and operated by Contextul ME LLC, a UAE-registered technology business headquartered in Dubai and founded in November 2025, with commercial activity across the UK, the GCC and the Americas. It is designed to sit alongside existing security infrastructure rather than replace it.
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Our ambition is simple enough: to make contextual data protection a standard part of how organisations use AI.
Frequently asked questions
What is AliasPath?
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AliasPath is AI data protection and governance software that uses contextual pseudonymisation to reduce the disclosure of sensitive information to AI models. It replaces protected values with realistic alternatives and can restore the originals within an authorised environment.
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How is AliasPath different from AI DLP?
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Traditional data loss prevention and many AI security products focus on identifying, monitoring or restricting sensitive information. AliasPath adds contextual transformation, allowing supported AI tasks to continue using pseudonymised information rather than necessarily blocking the interaction.
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Does AliasPath work with ChatGPT, Claude, Gemini and Microsoft Copilot?
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AliasPath is designed to support multiple AI models and applications. Actual compatibility depends on the product, integration route and deployment configuration. Supported workflows are confirmed during technical scoping.
Does AliasPath prevent every type of AI data leak?
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No security product can guarantee this. AliasPath reduces specified data exposure risks by transforming protected information before disclosure through supported routes. Its effectiveness depends on detection coverage, configuration, integration and the nature of the information involved.
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Does pseudonymisation make information anonymous?
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Not necessarily. Under GDPR and similar privacy frameworks, pseudonymised information can remain personal data. AliasPath is a technical safeguard intended to support data protection and governance, not a substitute for an organisation’s legal obligations.
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How do I get started with AliasPath?
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Book a 30-minute technical demonstration with the founding team. We then scope the workflows, models and data categories involved and agree a pilot on a real, sensitive workflow. AliasPath Desktop licences can be bought directly online.
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Can AliasPath be integrated into existing software?
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Yes. The AliasPath API allows developers and technology providers to incorporate contextual data protection into supported applications and workflows.
Key facts
Company name
AliasPath™
Operator
Contextul ME LLC (UAE-registered)
Type
AI data protection and governance software
Founded
November 2025
Founders
Rob Westmacott (CEO), Darren Wray (CTO)
Headquarters
Dubai, United Arab Emirates
Markets
UK, GCC, Americas, international
Website
Core offering
Contextual pseudonymisation: sensitive values are replaced with realistic aliases before reaching an AI model and restored within the authorised environment
Products
AliasPath™ Agent, AliasPath™ Desktop, AliasPath™ API, Privacy Proof, AI Risk Assessment
Detection coverage
2,003 patterns across 61 countries
Pricing
AliasPath™ Desktop $299 per licence per year; Agent per seat per month; API (contact)
Contract terms
Desktop licensed annually; Agent and API terms agreed per deployment
Support
Direct access to the founding team through scoping, pilot and deployment; service levels agreed per engagement
Communication
Email info@contextul.io; phone +44 7380 193014; 30-minute technical demonstrations
Category
AI data security, AI DLP, contextual pseudonymisation
Social
LinkedIn: Rob Westmacott; LinkedIn: AliasPath; LinkedIn: Darren Wray; LinkedIn: Paul Hartzell