SecureAI Guardian reads what a prompt actually means — not just which keywords it contains — and scores it across 9 detection layers before it ever reaches your AI model.
SecureAI Guardian sits between your users and your AI models, reading intent, scoring risk, and logging every decision — without adding meaningful latency.
Keyword filters catch what they've seen before. SecureAI Guardian is built around actual comprehension, so novel attacks and disguised requests don't slip through.
Prompts are read for real meaning and intent using a connected AI model — local via Ollama or cloud-hosted — not just scanned for trigger words.
Every prompt passes through tokenization, behavioral analysis, semantic relationships, and pattern matching before a verdict is reached.
Every decision comes with the specific rule that triggered it, so you can explain any Allow, Warn, Restrict, or Block to an auditor.
Every analysis is logged with timestamp, risk score, and reasoning, private to each signed-in account and ready to export.
Run entirely on your own hardware with Ollama for full data control, or use the built-in cloud backend so it works for every visitor instantly.
Every user signs in with their own account. History, settings, and results never mix between people using the same deployment.
Nothing gets Allowed, Warned, Restricted, or Blocked without a governance rule attached to it — so security teams can explain outcomes instead of guessing at a black box.
Tokenization, behavioral indicators, semantic relationships, contextual framing, and pattern matching all run on every single prompt — in real time, not on a delayed batch job.
Every prompt resolves to a single 0–100 risk score, mapped transparently to a governance outcome — no hidden weighting, no unexplainable model confidence number.
Alongside every score, the AI model writes out exactly why it reached that conclusion — in language a non-technical reviewer can actually read and trust.
Private per-account data, a permanent governance trail, and exportable logs make this suited for organizations that need to demonstrate control over AI usage.
The same pipeline runs on every single request, whether it's a test in the dashboard or live traffic from your application.
A prompt is entered manually or arrives through your application, exactly as a user or system wrote it.
A connected model interprets intent — recognizing disguised requests, roleplay framing, and social engineering, not just flagged words.
Tokenization, behavioral indicators, semantic relationships, and pattern matching each contribute to a single risk score and category.
Allow, Warn, Restrict, or Block is returned instantly, with the governance rule applied and a permanent record in your audit log.
Real-time risk scoring, audit history, and governance status — all inside the dashboard your team signs into every day.
Start free on your own infrastructure, or scale up when you need managed cloud AI for every visitor.
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