CattleGrid

CIO / IT Manager

The stake

Shadow AI is not a future risk your organisation is planning against. It is a current condition. 71% of UK employees are using AI tools their employer has not approved, and 51% do so at least weekly (Microsoft/Censuswide UK Shadow AI Survey, October 2025, n=2,003). Separate research puts the proportion of UK organisations with no controls over what data leaves through those tools at 83% (BlackFog/Sapio Research, November 2025, n=1,000 UK organisations).

For most organisations this gap is invisible until an incident, an audit, or a client due-diligence questionnaire forces the question. When it does, the IBM Cost of Data Breach Report 2025 puts the additional cost of a breach where shadow AI was involved at £498,000 over the baseline, against an average UK breach cost of £3.29 million. The report the board asks for at that point is usually the one nobody built in advance — and the person asked to produce it, after the fact, is usually IT.

The practical problem is not that this is hard to explain in principle. It is that "we need an AI governance layer" tends to arrive at board level as an abstraction, and abstractions are difficult to budget, staff, or schedule against. What boards actually want to know is what it costs, what it touches, and how long it takes.

What CattleGrid actually does

Deployment is a URL change. CattleGrid sits as a transparent proxy between your applications and the AI providers they call. The only change your engineering team makes is the base URL each request is sent to — headers, request bodies, authentication, and response handling all pass through unchanged. It works across OpenAI, Anthropic, Google Gemini, and Mistral, plus any provider that exposes a standard OpenAI-compatible API, so you are not locked into governing a single vendor's traffic.

Rules run in under a millisecond, in-process, with no external calls. Content inspection happens inline, using regex and keyword pattern matching evaluated against every request before it leaves your environment. Twenty-eight pre-built templates cover UK-specific PII (National Insurance numbers, NHS numbers, postcodes, passport numbers), financial data (sort codes, account numbers, card numbers with checksum validation), and credentials (API keys, AWS keys, private key headers). Each template ships in a standard and a context-aware variant, the latter using keyword proximity and pattern exclusion to cut false positives. Rules can block, redact, warn, or log, in that order of severity, and every rule can be scoped to specific providers.

Test Bench lets you see the outcome before it's live. Paste sample content — a realistic prompt, a test NI number, an edge case that shouldn't match — select the rules you want to check, and see exactly what would trigger and what the redacted output would look like, without a single request touching real traffic. It is the step that turns "trust us" into something you can verify yourself before enabling a rule for your organisation.

Rate limiting and visibility sit in one place. Five pre-configured tiers — Free, Starter, Professional, Enterprise, and Unlimited — enforce per-minute, per-hour, per-day, and per-month ceilings per API key, and changes to rules, providers, or limits take effect across live traffic within one to two seconds — no redeploy required. The dashboard shows request volume, block rate, top triggered rules, and active alerts in real time, so visibility does not depend on someone remembering to pull a report.

Team management matches how IT actually delegates. Four roles — Owner, Admin, Manager, Viewer — govern who can change what, with email or bulk CSV invites and ownership transfer built in. Every configuration change is written to an immutable audit log, cryptographically hash-chained so a record cannot be altered without the tampering being detectable — useful when the question is not just "what happened" but "who changed the rule, and when."

What this looks like once it's running

An organisation running CattleGrid can answer the "what does this involve" question with a deployment timeline measured in a URL change, not a project plan. It can show, rather than assert, what a given rule would have caught, because Test Bench makes that checkable before anything goes live. And it has an answer ready the next time a client, an auditor, or a board member asks who has visibility over what staff are sending to AI tools — because the audit log already has that answer, timestamped and tamper-evident, before the question is asked.

What CattleGrid does not do

CattleGrid inspects outbound AI API traffic — the input layer. It does not inspect, analyse, or govern AI responses, and it is not a substitute for a broader SIEM or DLP deployment. It governs AI traffic sent through API calls; it does not extend to AI tools accessed directly through a browser, so a member of staff visiting a consumer AI tool's website directly sits outside what API-layer interception can see. It does not conduct penetration testing, vulnerability assessment, or security audits, and it does not produce ISO 27001 ISMS documentation — those remain separate workstreams CattleGrid's evidence can support but not replace.

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