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Guardrails Policy · Privacy Security

Vigil Guard Enterprise

Vigil Guard Enterprise is an AIDR platform for security, platform and compliance teams. It inspects every prompt and every model response in real time, then returns ALLOW, SANITIZE or BLOCK. Everything runs on your infrastructure, air-gapped if needed.

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Overview

What is Vigil Guard Enterprise?

Vigil Guard Enterprise, shortened to VGE, is an AIDR platform: AI Detection and Response, a category its publisher places alongside EDR for endpoints and NDR for networks. Note that Enterprise here belongs to the product name itself, and is separately the name of the highest pricing tier. The starting argument is that natural language has become an attack surface: data, instructions and interaction all travel down a single channel, and the model cannot tell a command from a payload. That boundary, the publisher argues, has to be enforced outside the model, in real time.

VGE sits between your applications and your LLM providers and inspects every prompt and every response. A single REST call fans out to six detection branches running in parallel: language detection, heuristic analysis, semantic analysis, an ML injection classifier, content moderation and Semantic Drift Detection. A weighted arbiter aggregates the signals into one verdict, ALLOW, SANITIZE or BLOCK, and personal data found inside otherwise allowed content is masked before the text moves on. The datasheet advertises a fast-mode SLA under 500 ms, with a median below 200 ms on short prompts.

Coverage is broad. PII recognition spans 20+ entity types, among them PESEL, NIP, REGON, SSN, AU Medicare, UK NHS, IBAN and Luhn-validated card numbers, in replace, hash or mask mode set per API key. Semantic Drift Detection scores prompts ON, NEAR or OFF_SCOPE against an AES-encrypted Scope Definition at three sensitivity levels. Moderation covers 9 safety categories through a dual-classifier architecture. A Chrome and Edge extension, deployable by GPO, Intune or Jamf, watches public assistants including ChatGPT, Claude, Gemini, Copilot, Perplexity, DeepSeek, Grok, Mistral, Meta AI and Bielik, and every event exports to Splunk, QRadar, Sentinel, Elastic or any syslog collector.

The distinguishing constraint is deployment. Everything runs as a Docker Compose stack on one Linux x86_64 host, models embedded in the images, CPU-only inference, no GPU, no outbound calls, full air-gap supported. Detection results are published against nine linked public benchmarks. The current release is 1.8.6, dated 24 August 2026.

What it does

  • Detect direct and indirect prompt injection, including instructions hidden in third-party content the assistant ingests
  • Detect and mask more than 20 types of personal data before they ever reach the model
  • Classify every prompt as ON, NEAR or OFF_SCOPE against the assistant's declared scope
  • Moderate generated content across 9 safety categories
  • Make Shadow AI visible: which employee sent what, when and from which department
  • Export every event to the SIEM in CEF or JSON
  • Apply a different detection and response policy per API key
Audience

When to use Vigil Guard Enterprise / When not to

A quick filter to help you decide if Vigil Guard Enterprise is the right fit.

When to use Vigil Guard Enterprise

  • Security teams that need visibility, control and a complete audit trail over every AI interaction in the organization, including the Shadow AI nobody approved
  • AI and platform teams responsible for securing LLM applications and autonomous agents without slowing delivery down
  • Risk and compliance functions that have to reduce AI risk, prepare for audits and show a GDPR-facing paper trail
  • Regulated or isolated environments (public sector, defense, healthcare, finance) where the cloud is not an option and, as the pricing page puts it, a single data leak is unacceptable
  • Polish- and English-speaking organizations, whose languages the models cover natively and whose national identifiers (PESEL, NIP, REGON) the PII engine recognizes

When not to use Vigil Guard Enterprise

  • Individuals and small teams looking for a self-service product: there is no online sign-up and no public price, and all three tiers end in a sales conversation
  • Anyone without a dedicated Linux server to spare: even a pilot needs x86_64 hardware with roughly 20 cores, 30 GB of RAM and 70 GB of free disk
  • Buyers who specifically want a hosted SaaS guardrail: despite one contradictory line in llms.txt, the platform installs on the customer's own infrastructure
  • Teams expecting a mobile app or a permanently free tier, since neither exists and the only free access is a 7-day trial
  • Organizations working mainly in German, French or Italian, which the pricing page itself describes as only partially covered
Get started

How to use Vigil Guard Enterprise

A typical end-to-end flow, from setup to results.

  1. Confirm a business email address and your company name on the install page to obtain the installation command
  2. Prepare the host: Linux x86_64, around 20 cores, 30 GB of RAM, 70 GB of free disk, Docker Engine with Compose v2, ports 80 and 443 free, cosign, and network access to Docker Hub
  3. Run the interactive eight-step installer, starting with pre-flight checks and EULA acceptance, then the hostname and the TLS certificate (self-signed or your own)
  4. Let the installer unpack the infrastructure into /opt/vigil-guard and pick a scaling profile, from prod-32-balanced to prod-256-balanced, or force one with --scaling-profile
  5. Let it generate secrets locally, pull the container images and verify them cryptographically, then start the stack; the first launch opens a 7-day trial of the full platform with no license key
  6. Reach the service URLs the installer derives: api.{host} for the REST API, app.{host} for the web dashboard
  7. Wire your own applications in: a REST call before and after each LLM interaction, or the asynchronous, type-annotated Python SDK with client.guard(prompt)
  8. Or wire the gateway in: add a block to your LiteLLM Proxy config.yaml, in pre_call and post_call mode, fail-closed by default
  9. Or use the ready-made developer pieces: the verified n8n community node on n8n Cloud or On-Prem, and the VGE CC-Guard sidecar for Claude Code, installed with npm install -g @vigil-guard/vge-cc-guard
  10. Roll the browser extension out by GPO, Intune or Jamf, then tune thresholds, weights and feature flags from the dashboard, which propagates to every worker without a restart
Quick read

Pros & Cons

Pros

  • Fully on-premise, air-gap capable and GPU-free, which is a direct answer for sectors where the cloud is simply excluded
  • Detection results are published against nine linked public benchmarks rather than merely asserted, so a third party can re-run them
  • One detection model, PromptGuard v1g, is released open-weight on Hugging Face, allowing the approach to be evaluated before any purchase
  • Five deployment patterns (browser, n8n, LiteLLM proxy, custom applications, batch) covered by one rules engine and one SIEM export
  • Semantic Drift Detection tackles out-of-scope use, a problem conventional guardrails do not address
  • Multilingual PII coverage including national identifiers rarely handled elsewhere, such as PESEL, NIP, REGON, AU Medicare and UK NHS numbers
  • A 7-day trial of the complete platform on your own infrastructure without a license key, on container images verified cryptographically with cosign and a pinned digest manifest

Cons

  • No public pricing at all: the three tiers each lead to a sales conversation
  • A high hardware entry ticket, since a pilot needs a dedicated Linux server with roughly 20 cores, 30 GB of RAM and 70 GB of disk
  • A very young company: the legal entity was registered on 16 April 2026, the site's first Wayback capture is 5 August 2026, and only one executive is named
  • No security certification is claimed anywhere, which is a visible gap given that the buyer being addressed is the CISO of a large account
  • No terms of service are published: the only legal document online is the privacy policy, the EULA surfaces only at install time, and there is no DPA and no named subprocessor
  • Technical documentation is not public, with neither a docs section nor an online API reference available
  • llms.txt announces a SaaS deployment that every other page contradicts, the site exists in English and Polish only, and product language coverage is uneven, with German, French and Italian described as partial
Pricing

Pricing & Plans

There is no permanently free plan and no published price. Vigil Guard lists three tiers, Starter, Growth and Enterprise, and none of them carries a figure, neither on the pricing page nor in the datasheets nor in the site's structured data; the page states only that “Licensing depends on deployment scope, environment, and security requirements.” The datasheet describes the commercial model as a subscription license activated from the dashboard. The sole free access is a 7-day trial of the complete platform, unlocked at first start-up without a license key, which presupposes that the installation command has already been obtained. Every tier ends in a conversation with the vendor: Start Pilot, Talk to Us or Contact Sales.

Starter, presented as “For pilots and small teams” and scoped to up to 100 users
  • unlimited AI agents
  • the six detection layers
  • prompt injection and jailbreak detection
  • PII detection and policy enforcement
  • coverage of ChatGPT
  • Claude and others
  • content moderation
  • the browser extension
Enterprise, the top tier and not to be confused with the product name Vigil Guard Enterprise, presented as “For regulated and mission-critical environments”
  • everything in Growth
  • plus unlimited users and environments
  • full on-premise and air-gapped operation
  • custom policies and integrations
  • support during security reviews and audits
  • compliance-ready logging
  • an SLA and dedicated support. Call to action: Contact Sales
Special offers — A 7-day trial of the complete platform, every feature unlocked, starting at first launch and requiring no license key · PromptGuard v1g, a 44M-parameter detection model, published free as open weights on Hugging Face so the approach can be assessed at no cost · No student, non-profit, startup or launch discount is announced anywhere on the site
Prices and plans listed above may evolve. Always check the official pricing page before subscribing.
Trust & Privacy

Data, GDPR & hosting

A consolidated view of how Vigil Guard Enterprise handles your data.

GDPR overview

GDPR is claimed explicitly and in several places: the home page headline, the Risk and Compliance block and llms.txt all describe the offering as GDPR-compliant. The privacy policy lists the full set of rights (access, rectification, erasure, restriction, portability, objection, withdrawal of consent), commits to a 30-day response and gives one point of contact, contact@vigilguard.ai. It also documents encryption in transit and at rest, and permits transfers outside the EEA under the European Commission's standard contractual clauses, which is a transfer clause for website data and not a statement about where the platform is hosted. The publisher is established in Poland, so no Article 27 representative is required. No DPO is named, no DPA is published and no certification of any kind is claimed. The product-side argument is structural: an on-premise install sends no data to the publisher.

Who owns the data?

Two perimeters have to be kept apart. On the marketing website, Vigil Guard is the declared controller of the data you submit through the contact form, reachable at contact@vigilguard.ai. On the product side the question barely arises: the entire platform runs on your own infrastructure as a Docker Compose stack, with no external API calls, no cloud telemetry and no phone-home mechanism, so your prompts, your logs and your policy configuration stay on your side. Detection models ship inside the container images and run locally on CPU. Scope Definitions are AES-encrypted at rest with key rotation, and the audit log keeps only a SHA-256 fingerprint, never the plain text. No terms of service are published; the EULA appears only at install time.

Reuse rights

On the website, form data (name, email, company, job title) is used to answer your enquiry, to send product communications, to improve the site and to meet legal obligations, on the basis of legitimate interest and, for marketing, of consent. The privacy policy states plainly that “We do not sell your personal data”; it is shared only with categories of providers (hosting, email), with professional advisers and with authorities where the law requires it, and analytics are described as privacy-respecting, with no third-party tracking cookies. Inside the platform, the reuse question turns around: nothing reaches the publisher, so the detection logs, the audit trail and the analytics database are yours to query, export and reuse without asking anyone. False positives your team flags are indexed in a local vector memory that adjusts future scores, with no model retraining; the PromptGuard v4 models are presented as trained on adversarial data the publisher generates itself.

Data retention & training

Retention summary
Two regimes apply. On the website, contact form submissions are kept for up to 24 months and deletion can be requested at any time; more generally, data is kept only as long as the stated purposes or the law require. Inside the platform, retention is yours to set: the datasheet presents it as configurable, every detection decision is written to an analytics database with a full audit trail that lives on your own infrastructure, and no retention period is published because the publisher never holds the data. Two details are worth knowing: the plain text of Scope Definitions is never logged, only its SHA-256 fingerprint, and the CC-Guard sidecar keeps a local JSONL audit log that does not store the raw output of a blocked tool call.
Trains on customer data
No
GDPR contact

Hosting summary

The platform is not hosted by the publisher at all. “The entire platform runs on your infrastructure as a Docker Compose stack”, on a Linux x86_64 host you control, with no external API calls, no cloud telemetry and no phone-home mechanism; a fully air-gapped installation is supported. All ML models ship inside the container images, and inference is local, on CPU, without a GPU. The only network access required, and only during installation, is to Docker Hub in order to pull and verify the images. Jurisdiction therefore follows your own hosting decision: no hosting country and no region is named anywhere on the site, which is why those fields are left empty here. The marketing website is a separate matter, served behind Cloudflare (104.21.8.187, AS13335, anycast), which tells you where the brochure lives and nothing about where your prompts are processed. The privacy policy's clause permitting transfers outside the EEA under standard contractual clauses applies to website form data only, and names no country.

Watch-outs

Things to keep in mind

Risks and trade-offs to weigh before adopting Vigil Guard Enterprise.

  • Do not confuse the names. vigilguard.com is a live and entirely unrelated company, VigilGuard, an EASM, vendor-risk and crisis-readiness platform whose domain dates from 2004, with no redirect either way. Three different products also carry the PromptGuard name: this publisher's VGE PromptGuard, Meta's Prompt-Guard, cited as a competitor on the home page, and an unrelated UK product
  • Enterprise is ambiguous here: it names both the product, Vigil Guard Enterprise or VGE, and the highest pricing tier. Read any quote or quotation carefully to see which one is meant
  • The llms.txt file advertises SaaS, self-hosted and hybrid deployment, in flat contradiction with every other page, which claims 100% on-premise operation with no cloud component
  • The detection figures (99.2%, 100%, 0.0%, 97.4%) are the publisher's own results on public datasets. The datasets are linked, which is more than most vendors offer, but no third party has re-run the measurements
  • No security certification is claimed. NVIDIA Inception, AI Chamber and CyberMadeInPoland are memberships, not certifications and not investments; the NVIDIA NeMo Guardrails integration is announced as work in progress rather than a shipped feature; and the distributor's certified engineers commit the distributor, not the publisher
  • The privacy policy covers the marketing website only, including its clause on transfers outside the EEA. It says nothing about how data is handled inside the platform running on your own infrastructure, which is your responsibility to document. Note also that the domain was registered on 6 October 2025, more than six months before the legal entity existed
  • The human risks deserve as much attention as the technical ones. A tool that returns ALLOW can quietly manufacture confidence, and moderation is fail-open by design, so it should complement human review and existing DLP controls rather than replace them. Shadow AI visibility also means employee-level monitoring, which carries its own workforce-trust and data-protection weight, and no dashboard substitutes for an AI-use policy and the training that makes staff able to judge a model's output for themselves
Setup

Setup & Integrations

Technical difficulty

Moderate, and firmly an IT job rather than an end-user one. Access to the install command is gated behind a business email and a company name. You then need a dedicated Linux x86_64 server with 30 GB of RAM, 70 GB of disk, Docker Engine and Compose v2, ports 80 and 443 free and cosign, plus an eight-step interactive installer whose pre-flight checks fail fast. You choose a hostname, a TLS mode and a scaling profile, and a self-signed certificate then has to be trusted on workstations. Day-to-day tuning is codeless from the dashboard, and developer-side integration is light.

Deployment

Web appBrowser extensionChrome extensionAPIPlugin

Integrations

N8n LiteLLM Claude Code Docker Splunk IBM QRadar Microsoft Sentinel Elastic SIEM Google Chrome Microsoft Edge Microsoft Intune Jamf Hugging Face ChatGPT Claude Google Gemini Microsoft Copilot Perplexity DeepSeek Grok Poe Mistral Meta AI Character.AI Bielik Z.ai

Supported languages

EnglishPolishGermanFrenchSpanishItalianPortugueseTurkishRussian
Company

Behind Vigil Guard Enterprise

Company name
Vigil Guard PSA
Founded
16/04/2026
Country of origin
🇵🇱 Poland
Headquarters
ul. Piękna 24/26A, 00-549 Warszawa, Poland
UBO
INFORMATION_NOT_FOUND
UBO country
INFORMATION_NOT_FOUND
Domain registrar country
🇺🇸 United States

Social

Official links

Resources

All the official URLs gathered for verification and reference.

Compare

Alternatives

Tools that compete with or complement Vigil Guard Enterprise.

L Lakera GuardM Meta Prompt-GuardL LlamaGuard-3P ProtectAIA AporiaB Bedrock GuardrailsA Azure Content Safety
FAQ

Frequently asked questions

What does AIDR mean?
AI Detection and Response. It is the category Vigil Guard claims for itself: runtime security for AI systems, presented as the counterpart of EDR for endpoints and NDR for networks, watching the prompts, the responses and the actions an agent takes.
Is the platform hosted by Vigil Guard?
No. Vigil Guard Enterprise installs on your own infrastructure as a Docker Compose stack, with no external API calls and no telemetry sent back to the publisher. One caveat worth flagging: the site's llms.txt file mentions a SaaS option, which every other page contradicts.
What hardware does it need, and is a GPU required?
No GPU: inference runs locally on CPU. The published prerequisites are a Linux x86_64 host with at least 30 GB of RAM and 70 GB of free disk, around 20 cores, Docker Engine with Compose v2, and ports 80 and 443 available.
Can I try it before committing?
Yes. The first start-up opens a 7-day trial of the complete platform with every feature unlocked and no license key. You first have to obtain the installation command by confirming a business email address and your company name, so it is not a self-service sign-up.
How much does it cost?
No amount is published anywhere on the site or in the datasheets. There are three tiers, Starter, Growth and Enterprise, and the license is described as a subscription activated from the dashboard. Pricing is stated to depend on deployment scope, environment and security requirements.
Which languages does it cover?
Polish and English are the strongest. Content moderation is native in 8 languages (Polish, English, French, Spanish, Italian, Portuguese, Turkish and Russian) and language detection spans 22 languages, while the pricing page describes German, French and Italian coverage as partial.
How do I connect it to my applications?
Four documented routes: a REST call before and after each LLM interaction, the Python SDK, the official LiteLLM guardrail added to your proxy configuration, or the verified n8n community node. A batch endpoint accepts up to 24 prompts in a single call.
What happens when a threat is detected?
A weighted arbiter aggregates the six detection branches into one verdict: ALLOW, SANITIZE or BLOCK. When personal data is found inside content that is otherwise allowed, it is masked before the text is passed on, according to the replace, hash or mask mode set for that API key.
Can I send the events to my SIEM?
Yes, natively. Events export in CEF or JSON over TCP and TLS to Splunk, IBM QRadar, Microsoft Sentinel, Elastic SIEM or any syslog collector, and each detection decision is logged with its full context.
Who is behind the tool, and is it certified?
The publisher is Vigil Guard PSA, based in Warsaw, Poland, and founded by Tomasz Bartel. No security certification is claimed anywhere on the site; the memberships it does display, such as NVIDIA Inception, are not certifications. There is no mobile app either.
Conclusion

Should you pick Vigil Guard Enterprise?

Vigil Guard Enterprise occupies a narrow and clearly stated position: runtime security for natural-language interactions, precisely where EDR, DLP and WAF are blind. The technical proposition holds together, with six detection branches behind a single REST call, one verdict, a rule set per API key, and the same event stream feeding your SIEM whether the traffic comes from a browser extension, an n8n workflow, a LiteLLM proxy or your own code.

Two things make it more checkable than most in this category. The detection figures are published against nine linked public benchmarks rather than merely asserted, and one detection model is released open-weight on Hugging Face, so the approach can be evaluated before any commercial conversation begins. The structural argument is the deployment model itself: a Docker Compose stack on your own Linux host, CPU-only, no outbound calls, air-gap supported. For public sector, defense, healthcare and finance, that is often the deciding factor.

The reservations are just as concrete. The company was registered in April 2026 and the site is only months old. There is no public price, no published terms of service, no DPA, no named subprocessor and no security certification claimed, which is a visible gap given the large-account CISO being addressed. Technical documentation is not public, and llms.txt contradicts the rest of the site by mentioning SaaS. The hardware requirement rules out casual evaluation.

Traction is nonetheless real: a distribution agreement with Oberig IT across 18 markets, an integrator partner, memberships in NVIDIA Inception, AI Chamber and CyberMadeInPoland, an official LiteLLM guardrail and a verified n8n node, with releases running from v1.5 in March 2026 to v1.8.6 in August 2026. Promising, and unusually transparent about how it measures itself; still to be judged on contractual and organizational maturity.