Watch a 5-Minute AI Data Loss Prevention Demo to see how AILeakShield helps prevent sensitive data from reaching AI prompts and discover which AI tools are being used across your organization.

Govern AI across your business.

Say yes to AI, safely. Discover every AI in use, control which ones are allowed, protect your data in them, and prove compliance, so your business can adopt AI without the risk.

Available through your IT provider or distribution.

Your team is already using AI. The question is whether it is protected.

Employees use AI because it helps them move faster. They summarize pasted text, rewrite emails, review pasted business information, draft policies, debug code, and brainstorm customer responses.

But when prompts include customer records, employee information, source code, credentials, contracts, protected healthcare information, financial data, or internal strategy, sensitive data can leave the business before security teams ever see the risk.

AILeakShield gives your organization a safer path: one approved AI workspace where employees can use AI with protection built into the prompt workflow. One solution to discover AI in-use and one solution to protect AI solutions already being used by your employees.

Sensitive data in prompts

Customer records, PII, payment data, employee details, contracts, credentials, source code, and internal strategy can all end up inside AI prompts.

Shadow AI blind spots

Teams often use personal AI accounts, browser tabs, and unapproved tools when the company does not provide a secure alternative.

Compliance pressure

Security, legal, privacy, and compliance leaders need a defensible way to govern AI usage.

AI adoption friction

Blanket bans slow down the business and push AI usage underground. Secure enablement gives employees a better option.

Why secure AI access matters now

0 %
49% of workers use AI tools without employer approval.
BlackFog, Shadow AI Research, 2026
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64% of respondents worry about inadvertently sharing sensitive information publicly or with competitors.
Cisco, Data Privacy Benchmark Study, 2025
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68% of breached organizations had no AI governance policy or were still developing one.
IBM, Cost of a Data Breach Report, 2026
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The average company experienced 223 monthly incidents of users sending sensitive data to AI apps.
Netskope, Cloud and Threat Report, 2026

AILeakShield helps businesses say yes to AI safely: discover every AI in use, control which tools are allowed, protect sensitive data in the approved ones, and prove compliance.

One platform

Govern AI end to end, from discovery to proof

Let your business adopt AI without the risk. Four steps, one console.

  • Discover
  • Control
  • Protect
  • Comply

Discover

See every AI your people use, including the ones others miss.

  • Desktop AI apps and coding agents, found through your RMM, with no agent to deploy
  • AI apps connected to Microsoft 365 through OAuth consent
  • AI used in every managed browser
  • A risk register, not a list: who trains on your data and where it is processed
How shadow AI discovery works

Control

Allow the AI you trust. Block the rest.

  • Real-time enforcement in every managed browser
  • Block unapproved AI at your firewall and in Microsoft 365 app consent
  • Tool approvals that write straight to enforcement

And, if you want, give people one sanctioned, safe place to use AI.

Protect

Keep sensitive data out of the AI you approve.

  • Inline DLP that warns or blocks before data leaves
  • Personal data, health data, credentials and source code
  • Your own sensitive terms: clients, projects and codenames
  • Prevention, not just alerts: nothing left to investigate
See ChatGPT DLP in action

Comply

Apply your compliance rules to approved AI, and prove it.

  • HIPAA, PCI DSS, GDPR, ISO 42001 and NIST AI RMF policies enforced on prompts
  • Built-in NIST AI RMF assessment and governance scorecard
  • Evidence, audit trail and staff attestation, ready for auditors
How AI governance works

How it works

Start by watching. Then discover, control, protect and comply.

Four steps, in the order you will actually live them, starting with two weeks where nothing is blocked at all.

Start by watching. Block nothing.

AILeakShield deploys in minutes through the tools you already have, browser policy and your RMM, and runs in monitor mode. For the first two weeks it blocks nothing and changes nobody’s workflow: it simply records what is already happening. Then you sit down with real numbers and decide what to enforce. One switch, and it is yours to flip.

  1. Discover

    Every AI in use, ranked by risk

    Browser AI, desktop AI apps and coding agents through your RMM, AI apps connected to Microsoft 365, and AI agents, in one risk register: which services train on what your staff paste into them, where each processes data, and whether a business tier exists to move to.

  2. Control

    Allow the AI you trust. Block the rest.

    Approve the tools you want to keep. Everything else is blocked or restricted in the browser, at your firewall and in Microsoft 365 app consent, in real time.

  3. Protect

    Keep sensitive data out of the AI you approve

    Plenty of tools will tell you an AI tool was used. That is an alert after the data has gone. AILeakShield inspects the prompt and warns or blocks sensitive content before it reaches the model, so there is nothing left to investigate.

  4. Comply

    Your obligations, applied to approved AI, and proved

    HIPAA, PCI DSS, GDPR, ISO 42001, the NIST AI RMF and your own rules, enforced on prompts. Every decision, every override and the reason given for it, plus a built-in NIST AI RMF assessment, governance scorecard and staff attestation: the record you hand an auditor.

Discovery covers the full catalogue of AI services. Enforcement covers the assistants your staff are most likely to reach for, including ChatGPT, Microsoft Copilot, Claude, Gemini and Perplexity, with everything else discovered and reported so you can decide what to do about it.

How AILeakShield is different from traditional AI DLP rollouts

Many AI DLP and enterprise security platforms are powerful, but they often require broader security architecture, browser controls, endpoint coverage, proxy routing, or long-term policy tuning. AILeakShield is built to give employees secure AI access now. See how AILeakShield compares with Microsoft Purview, Netskope, Zscaler and other AI security tools.

Solution

Common approach

What that can mean for customers

Netskope

Enterprise SSE, CASB, DLP, app risk scoring, traffic controls, & AI governance.
Strong for companies already standardizing on a broader SSE or SASE program, but usually part of a larger security architecture.

Zscaler

Zero Trust Exchange, DLP controls, AI app policies, prompt visibility, and browser isolation options.
Strong for organizations already routing internet access through Zscaler, but often tied to proxy, isolation, and traffic-control strategy.

Nightfall AI

AI-native DLP across SaaS, endpoints, browsers, email, and AI apps.

Strong broad DLP coverage, but browser and endpoint coverage can require plugins, agents, rollout planning, policy tuning, and ongoing updates.

Microsoft Purview

Microsoft-native DLP, Defender for Cloud Apps, endpoint DLP, Copilot controls, sensitivity labels, and policy enforcement.

Strong for Microsoft-heavy environments, especially Microsoft 365 and Copilot, but broader AI coverage depends on Microsoft licensing, configuration, extension, and endpoint setup.

Palo Alto Networks

Enterprise DLP, Prisma Access, NGFW, CASB, and security policy controls for AI apps such as ChatGPT.
Strong for Palo Alto customers, but often tied to firewall, Prisma, CASB, traffic inspection, and security-policy architecture.

Proofpoint

Human-centric DLP, endpoint/cloud telemetry, browser extension controls, blocking, redaction, and user coaching.
Strong for insider-risk and broad DLP programs, but can involve endpoint telemetry, browser controls, user behavior policy, and training workflows.

How AILeakShield is different

Solution

Common approach

Netskope

Enterprise SSE, CASB, DLP, app risk scoring, traffic controls, & AI governance.

Zscaler

Zero Trust Exchange, DLP controls, AI app policies, prompt visibility, and browser isolation options.

Nightfall AI

AI-native DLP across SaaS, endpoints, browsers, email, and AI apps.

Microsoft Purview

Microsoft-native DLP, Defender for Cloud Apps, endpoint DLP, Copilot controls, sensitivity labels, and policy enforcement.

Palo Alto Networks

Enterprise DLP, Prisma Access, NGFW, CASB, and security policy controls for AI apps such as ChatGPT.

Proofpoint

Human-centric DLP, endpoint/cloud telemetry, browser extension controls, blocking, redaction, and user coaching.

Solution

What that can mean for customers

Netskope

Strong for companies already standardizing on a broader SSE or SASE program, but usually part of a larger security architecture.

Zscaler

Strong for organizations already routing internet access through Zscaler, but often tied to proxy, isolation, and traffic-control strategy.

Nightfall AI

Strong broad DLP coverage, but browser and endpoint coverage can require plugins, agents, rollout planning, policy tuning, and ongoing updates.

Microsoft Purview

Strong for Microsoft-heavy environments, especially Microsoft 365 and Copilot, but broader AI coverage depends on Microsoft licensing, configuration, extension, and endpoint setup.

Palo Alto Networks

Strong for Palo Alto customers, but often tied to firewall, Prisma, CASB, traffic inspection, and security-policy architecture.

Proofpoint

Strong for insider-risk and broad DLP programs, but can involve endpoint telemetry, browser controls, user behavior policy, and training workflows.

How AILeakShield is different

AILeakShield governs AI end to end without another long enterprise DLP rollout. It deploys in minutes through the tools you already have, browser policy and your RMM, and is live in two weeks.

Built for security-conscious teams.

AILeakShield is hosted on Microsoft Azure infrastructure in continental United States Azure regions. The service is built for businesses that want secure, approved AI access with Microsoft SSO, prompt-level protection, usage controls, and transparent security practices. 

A SOC 2 Type 2 Data Center with AILeakShield SOC 2 audit available every year.

Microsoft Azure infrastructure

Hosted on Microsoft Azure infrastructure in continental United States Azure regions.

Microsoft SSO

Microsoft single sign-on is included in every plan.

CSA STAR

CSA STAR trust category included at launch.

Daily prompt text deletion

Prompt text and contextual AI inputs are removed at the end of each day.

Azure-backed trust

Built on Azure datacenters with independent compliance programs, including SOC, ISO, CSA STAR, PCI DSS, HIPAA/HITECH support, and FedRAMP for applicable Azure services.

Built for teams that need AI and security.

1

Security teams

Reduce AI data leakage and shadow AI exposure.

2

Compliance teams

Support AI governance, auditability, and policy enforcement.

3

Healthcare organizations

Help prevent PHI and patient information from being pasted into unmanaged AI tools.

4

Financial services teams

Help protect client records, account data, financial information, and internal analysis.

5

Legal teams

Help prevent contracts, privileged information, and case details from entering public AI tools.

6

Technology teams

Help protect source code, API keys, credentials, product plans, and customer data.

For MSPs and distribution

Built for MSPs and distribution partners

Sold through IT providers and distribution. We don't compete with our partners on price.

Multi-tenant partner console

Manage every client from one console, with per-client isolation built in.

Policy templates you push

Build a policy once and push it to every client, adjusting per client where needed.

Discover across your whole book

Find AI in use across all your clients through your RMM and Microsoft 365 GDAP access.

You own the customer

The client relationship stays with you. We support you, not compete with you.

Live in two weeks

Deploys in minutes through the tools you already have, browser policy and your RMM, then two weeks of monitor mode.

No seat minimum

Start with one client or one department and grow from there.

Packaging

One platform. Everything included.

Discover, Control, Protect and Comply in every subscription, with an optional sanctioned AI workspace. Pricing is available through your IT provider or distributor, including TD SYNNEX.

Common questions about shadow AI, AI data loss prevention and compliance

What security, IT and compliance teams ask before they roll this out.

The problem

What is shadow AI?

Shadow AI is any AI tool your staff use without IT approval: a personal assistant account, a coding agent, an image or voice generator, a browser extension, a direct call to a model API. It is rarely malicious. People reach for whatever helps them finish the work, and most organisations find services running across a dozen or more categories that nobody signed off. See how shadow AI discovery works.

How do I find out which AI tools my employees are already using?

Deploy the browser extension by policy and watch for two weeks. It records every AI service reached, without blocking anything, and ranks what it finds by risk rather than by popularity. For tools that never open a browser, import a DNS or proxy log and those appear in the same inventory.

Can I just block AI tools with a firewall?

You can block the domain, and staff will use a personal device or a tool you have not heard of yet. A firewall decides whether a site is reachable; it cannot see what someone typed, so it cannot tell an approved research question from a customer list pasted into a chat box. Blocking without a sanctioned alternative moves the activity somewhere you have no visibility at all.

How is this different from the DLP we already have?

Traditional DLP watches files, email and endpoints. An AI prompt is none of those: it is an HTTPS request to a domain most policies already permit, so the content is invisible to tools that inspect at the network or file layer. AILeakShield inspects the prompt itself, in the browser, before it is sent.

Compliance

What compliance requirements does AILeakShield support?

It provides the control and the evidence that regulated organisations need when staff use AI: preventing regulated data from reaching a third-party model, and producing a record of what was detected and decided. That maps onto the obligations in:

  • HIPAA: protected health information
  • PCI DSS: cardholder and payment data
  • GDPR and UK GDPR: personal data, including transfers outside your region
  • GLBA: customer financial information
  • CCPA / CPRA and other US state privacy laws
  • SOC 2: confidentiality and privacy criteria
  • ISO 27001 / 27701: information security and privacy controls
  • CMMC, ITAR and export control, controlled and classified material
  • FERPA: student records
  • NIST AI RMF and the EU AI Act: AI inventory and governance duties

Ready-made policy presets ship for HIPAA, PCI, GDPR, GLBA and defense, so a regulated organisation is not starting from a blank form.

Does AILeakShield make us HIPAA or PCI compliant?

No, and be wary of any vendor that says otherwise. Compliance is a property of your organisation, not of a tool. What AILeakShield does is implement a specific control, regulated data does not reach an unapproved AI service, and produce the evidence that the control was operating. Auditors ask for both. This is one component of a larger program to be PCI or HIPAA compliant. We offer additional services through cybersecurityservices.com our consulting practice.

What sensitive data can it detect, and can we control each type?

Six categories, each set independently to block, warn or allow:

  • PII: names, addresses, government identifiers, dates of birth, contact details
  • PHI: diagnoses, treatment and other protected health information
  • Financial: card numbers, account and routing details
  • Credentials: passwords, API keys, tokens, connection strings
  • Classified: controlled and marked material
  • Network: internal hostnames, addresses and infrastructure detail

So a hospital can block PHI outright while only warning on financial data, and a payments business can do the reverse. The same settings apply in the browser and in the secure workspace, so there is one policy rather than two.

Can we add our own sensitive terms?

Yes. Project codenames, client names, unreleased product names, internal system names, anything that is confidential to you but looks unremarkable to a generic detector. These are treated as your own category and never leave your tenant.

Does this help with SOC 2 or ISO 27001?

It gives you an implemented control and an audit trail for it, which is what those frameworks ask for. AI use is increasingly raised under confidentiality criteria and third-party risk, and “we have a policy” is a weaker answer than a record of what was detected, what was blocked, and who overrode what and why.

What about the EU AI Act and the NIST AI Risk Management Framework?

Both start from the same place: knowing which AI systems are in use. The risk-ranked inventory is that starting point, and the policy and audit records support the governance duties that follow. NIST AI RMF is voluntary and has no certification, so treat any “AI RMF certified” claim, from us or anyone else, with suspicion. We say aligned with, not compliant.

How it works

How do I stop employees pasting sensitive data into ChatGPT?

Detection alone will not: an alert arrives after the data has already reached the model. AILeakShield inspects the prompt in the browser and blocks or warns before it is sent, according to the policy you set for each category of data. The same policy applies across the assistants your staff use, not one of them. Learn more about ChatGPT DLP.

Will AILeakShield block AI for my whole company?

Not unless you choose to. It starts in monitor mode, where nothing is blocked and nothing changes for staff. You decide what to enforce after seeing your own numbers, and giving people a sanctioned workspace usually works better than a ban, which simply moves the activity somewhere you cannot see it.

What about AI tools that never open a browser?

Coding agents, desktop assistants and anything calling a model API directly are outside what a browser extension can see. Import a DNS or proxy log and they join the same risk-ranked inventory, so the picture covers the estate rather than just the tabs.

What happens when someone tries to send something sensitive?

It depends on the category and the rule you set. Blocked content does not leave the browser. A warning explains what was detected and why, and if the person proceeds anyway they are asked for a reason, which is recorded, so a judgement call becomes evidence rather than an argument later.

Rollout

Do employees have to install anything?

No. The browser extension is deployed by policy through Intune, Group Policy or your MDM. Nobody installs, signs in or configures anything, and browsers begin reporting within a minute of the policy applying.

Which browsers are supported?

Chrome, Edge, and Firefox are verified end to end for managed deployment. Safari is available on request: talk to us about either before you plan a rollout around them.

Does it work for remote and hybrid staff?

Yes. Protection travels with the browser rather than the network, so there is no VPN to route through and no difference between someone in the office and someone at home.

Trust and evidence

Can AILeakShield see our prompts?

Prompt text is not retained. Inspection happens in the moment, and stored records keep the decision and the category rather than the content: a product that leaks the data it was bought to protect would defeat its own purpose.

Are our prompts used to train AI models?

No. Work done in the secure workspace is not used to train models. That is a large part of why a sanctioned destination reduces risk while a personal account on a consumer tier increases it: several of the services your staff reach for do train on what is pasted into them by default.

What does this give an auditor?

A record of what was detected, which policy applied, what was decided, and the reason given whenever somebody overrode a warning. That answers “how do you govern AI use” with evidence rather than an intention, which is the form the question usually takes.

Say yes to AI, safely.

AILeakShield discovers all the AI in your environment, blocks the AI tools you have not approved, and keeps sensitive data out of the prompts sent to the ones you have.