DeepInspect vs HiddenLayer: Runtime AI Security Compared

DeepInspect evaluates routed HTTP requests between authenticated users or agents and LLMs before the provider receives them. HiddenLayer began with model scanning and adversarial-ML detection, then expanded into runtime detection. The buyer decision turns on the control point: a per-request policy decision and evidence record, an artifact scan before deployment, or a detection surface for anomalous model behavior.

TL;DR

DeepInspect is an identity-aware HTTP-proxy that authenticates the caller against the corporate IdP and commits per-decision records on every request. HiddenLayer's AIDR (AI Detection & Response) covers runtime telemetry and adversarial-ML detection, and the Model Scanner covers artifacts before they enter production. Pick DeepInspect if the program centers on identity-bound enforcement records under Article 12 or HIPAA audit obligations. Pick HiddenLayer if adversarial ML detection and model artifact scanning are the primary controls. Programs with both requirements commonly use both surfaces.

Where DeepInspect sits

DeepInspect sits inline on the HTTP path between authenticated users or agents and any LLM. The proxy terminates TLS at the inspection layer, authenticates against the corporate IdP, classifies the prompt content, evaluates policy against identity and classification, and commits a per-decision audit record before the model receives the request. Each record carries identity, classification, policy version, decision, timestamp, and an integrity signature on a tamper-evident series.

The product is purpose-built for the runtime enforcement boundary. Model artifact inspection belongs upstream in the registry or pipeline.

HiddenLayer: where it sits

HiddenLayer ships two named surfaces. The Model Scanner inspects model artifacts at the registry or pipeline boundary, catching malicious payloads in Pickle files, malicious LoRA adapters, and known-vulnerable dependency patterns. AI Detection & Response (AIDR) monitors runtime AI traffic and inference telemetry, looking for adversarial ML patterns including model evasion, model extraction, membership inference, and prompt injection variants.

HiddenLayer's adversarial-ML lineage shows up in the AIDR detection catalog. The platform's strength is the breadth of adversarial-ML detections, including model-extraction patterns the prompt-injection-focused tools do not natively catch. The audit record on the AIDR side is shaped around the detection event, with prompt content and policy state attached when the integration is wired through.

Comparison criteria

The first comparison axis is the runtime control point. DeepInspect evaluates routed HTTP LLM requests inline. HiddenLayer AIDR receives telemetry and detection signals, while Model Scanner works on artifacts before deployment.

Identity evidence follows the deployment path. DeepInspect uses the caller context available at the proxy for each policy decision. A HiddenLayer integration needs to carry identity into its telemetry.

The products also have different primary jobs. DeepInspect focuses on authorization and a per-decision record for model traffic. HiddenLayer emphasizes adversarial-ML detection and scanning suspicious model artifacts. Both can participate in multi-provider programs through their configured routes and integrations.

Audit evidence remains a separate consideration. DeepInspect writes a structured decision record for each routed request. HiddenLayer detection events describe observed model-risk signals with the context supplied by the integration.

Pick HiddenLayer if

• The program's primary risk model centers on adversarial ML against production models, including model extraction, evasion attacks, or membership inference.
• Your artifact pipeline runs many self-hosted open-weight models and needs scanner coverage.
• Detection and response (alert, triage, response playbook) matter more than per-request enforcement at the boundary.
• The team can own the integration that carries identity from the application to detection telemetry.

Pick DeepInspect if

• The program centers on identity-bound per-request records under EU AI Act Article 12, Article 19, or HIPAA Security Rule audit obligations.
• The deployment spans multiple LLM providers on the same policy surface and the record series needs to be canonical.
• Enforcement happens at the request boundary before the model receives the request, not after the model returns the response.
• The IdP integration belongs at the inspection boundary rather than inside each application team's code.

Combining the two

A program with both adversarial-ML risk and audit record obligations runs the two products on different surfaces. HiddenLayer's Model Scanner inspects artifacts at the registry boundary. DeepInspect enforces policy at the runtime HTTP boundary and carries the canonical record series. HiddenLayer's AIDR can supply additional adversarial-ML detections that feed into the same SIEM or SOAR pipeline the DeepInspect records flow into. The two products report into the same audit program through different evidence pipelines.

Regulatory framing

EU AI Act Article 12 calls for automatic event recording in high-risk AI systems. The current obligations and timing depend on the system's role and use case, so teams should map their evidence plan to the operative text rather than treat a vendor feature list as a compliance result. HiddenLayer's Model Scanner documentation is useful when the evidence question starts at a model artifact; runtime request records answer a separate question.

An auditor reviewing a runtime decision needs the requester, the applicable policy, the prompt classification, and the returned outcome. DeepInspect's routed HTTP proxy captures the policy decision at that point. HiddenLayer's adversarial-ML detections describe observed model-risk signals, which complement the request evidence without replacing it.

Pricing approach

Both vendors quote against the specific deployment after scoping. DeepInspect prices per protected endpoint and request volume tier. HiddenLayer prices across the Model Scanner and AIDR modules with platform tiers. Public price lists are not available for either product.

DeepInspect

DeepInspect is the runtime HTTP-proxy enforcement gateway. The proxy authenticates the caller against the corporate IdP, classifies the prompt content, evaluates policy against identity and classification, and commits a per-decision audit record before the response returns to the application. The record gives the audit program a request-level evidence surface, detailed in AI audit-log chain of custody.

For programs comparing DeepInspect to HiddenLayer, the framing I find useful is to separate the artifact question from the runtime enforcement question and pick the placement that produces the record series the audit program references. The proxy placement is the one that produces identity-bound records across multiple LLM providers on a shared series. DeepInspect vs LLM Guard covers a related request-boundary decision.

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