How it works
Full visibility. Zero disruption.
RAIDS is a real-time monitoring layer for AI in production. It reads input and outputs only, no access to model internals, training data, or your code, and no cooperation required from whoever built the model. That independence is the point: it’s why RAIDS works on any system.
A full walkthrough of RAIDS: from initial connection to real-time detection and the evidence trail it builds for auditors, regulators and enterprise customers.
The platform, step by step
Six stages, from initial connection to a complete compliance trail.
Connect
Name your system, upload a baseline of normal interactions, and connect through the API. RAIDS handles three kinds of systems, each with its own detection approach: large language models, structured or tabular models, and time-series models.
Learn
RAIDS learns what normal looks like for your system specifically, no shared benchmark, no industry-wide rule set. Every interaction from then on is measured against that baseline.
Detect
Deviations are scored and classified in real time: sudden breaks, like a jailbroken chatbot or a hallucinated answer, and slow drift, like a credit model skewing gradually over months. Even an attack your model successfully blocked gets flagged, because the interaction itself was abnormal, regardless of outcome.
Explain and prove
Every detection shows why it was flagged: which behaviors deviated, by how much, and how far outside the normal range they fell. The full monitoring record becomes your evidence trail for auditors, regulators, and enterprise customers.
Features
The core capabilities, at a glance.
Non-invasive by design
Works with any AI system by analyzing inputs and outputs only. No model access, no training data, no vendor cooperation required. Data can be anonymized before monitoring.
A baseline for every system
RAIDS learns what normal looks like per system and detects both sudden anomalies and gradual drift against it.
Explanations, not just alerts
Each flagged interaction includes the reasons it was flagged, the behaviors that deviated, and how far outside the normal range they fell. Investigations start with answers, not raw logs.
One dashboard, every system
Live activity, detections, and trust scores across your whole environment in one place, filterable by time range so you can see how a system behaves over days or months, not just right now.
Real-time detection
Deviations are scored and flagged the moment they happen, not hours later in a report.
Sharper with feedback
Your team validates detections directly inside the platform, and that feedback refines accuracy over time.
Yes. RAIDS is built for AI vendors and builders, whatever you’re building on top of, wherever it’s deployed. If you’re shipping AI in production, RAIDS monitors it.
Large language models, structured or tabular models, and time-series models, each with its own detection approach. If it’s making decisions in production, RAIDS can watch it.
No. RAIDS analyzes inputs and outputs only, never model weights, code, or training data, and monitored data can be anonymized first. That's a deliberate design choice: it's what keeps the monitoring independent.
It turns every interaction with your system into measurable behavioral signals and compares them against a learned baseline of normal behavior. When something doesn't reconcile with that baseline, it's classified and scored by severity in real time.
Observability tracks technical performance and needs model access. Security tools defend against external attacks. GRC platforms manage documentation and workflow. RAIDS covers the gap between them: independent monitoring of how your AI behaves once it's live, producing evidence those other tools can use. It complements a platform like Drata rather than replacing it.
No. Compliance is your organization’s responsibility, RAIDS provides the continuous monitoring evidence that supports it. Both frameworks expect ongoing oversight, not a one-time assessment, and that's what RAIDS automates the evidence collection for. For specific provisions, like ISO 42001 A.6.2.6 or EU AI Act Article 72 (the Post-Market Monitoring System obligation), RAIDS is your real-time monitoring solution.
Name your system and select its type, provide a baseline (upload past interactions or connect live), and finish the API integration using the integration guide. Monitoring runs in the background, it doesn't sit in the inference path or change how your model runs. Support is available throughout at support@raidsai.ai.
Connect live instead. RAIDS establishes the baseline by observing real traffic from day one.
An alert with the classification, severity, and the reasoning behind it: which behaviors deviated and by how much. Your team investigates from the explanation, not raw logs, and can feed back on any detection to tune it further.
Partnerships
Working with the Partners your clients already trust
See the evidence, not the pitch
One demo shows you the dashboard, the trust score, and the evidence trail your buyers will eventually see too.
