Home / Compare / PolicyLayer vs DeepInspect

PolicyLayer vs DeepInspect

Both are inline gateways for AI, but they watch different traffic. PolicyLayer governs the MCP tool calls your agents make (the actions they take on your systems). DeepInspect governs the prompt and response traffic flowing to LLM providers, with data-loss prevention and compliance forensics. Here is where each one fits.

GOVERN YOUR MCP CALLS → Instant setup, no code required.

The short version.

Two inline gateways, two surfaces. One watches what leaves in a prompt; the other watches what an agent does with a tool.

PolicyLayer

PolicyLayer is the gateway your MCP traffic runs through. Connect your servers and every tool call is checked against deterministic, deny-by-default policy before it executes: allow, deny, rate-limit, or require approval, with argument-level rules, per-identity scopes, and a per-call audit log. It is purpose-built for MCP, with a server and tool directory and per-tool risk classification.

DeepInspect
Inline DLP and governance for AI usage

DeepInspect is an inline gateway for AI usage. It sits between users or apps and the model provider, detects sensitive data (PII, PHI, PCI) in prompts and responses, and redacts, tokenizes, or blocks it, then writes signed forensic records mapped to regulatory frameworks. It also offers model cost routing and agent and MCP governance.

Side by side.

The dimensions enterprise teams weigh when they choose where to put an AI gateway.

  PolicyLayer DeepInspect
Primary surface MCP tool calls: the actions an agent takes on your systems Prompt and response traffic to LLM providers: what the model sees and returns
What it inspects The tool and its arguments, against your policy Prompt and response content for sensitive data (PII, PHI, PCI)
Primary action Allow, deny, rate-limit, or require approval on the call Redact, tokenize, or block sensitive content in the payload
Policy model Deterministic, deny by default, argument-level rules in a visual editor and as code Deterministic detectors plus natural-language policies evaluated by a model at request time
MCP coverage MCP-native: gateway, server and tool directory, per-tool risk classification Tool calls governed as enforcement events within a broader model-governance product
Model cost routing Out of scope; PolicyLayer governs tool calls, with a token-cost directory for context Tier-based model routing, failover, and per-actor token accounting
Audit Every tool call logged with the tool, its arguments, and the decision HMAC-signed, tamper-evident forensic records mapped to compliance frameworks
Compliance framing MCP security, risk, and incident context, plus a compliance reference Heavy framework mapping: EU AI Act, HIPAA, 21 CFR Part 11, GLBA, PCI DSS, SOC 2
Buyer Platform and security teams running MCP agent fleets CISOs and compliance teams governing AI usage in regulated industries
Deployment Hosted control plane and gateway; route your MCP servers through it Self-hosted, SaaS, or air-gapped, in front of the model provider
Best fit Governing what agents do through MCP servers Stopping sensitive data leaving in prompts and proving model-usage compliance

Where each one fits.

Choose PolicyLayer when

Your risk is agent actions, not prompt content

Agents refund, merge, run SQL, and change infrastructure through MCP servers, and you want a deterministic check on the call before it runs.

You run MCP servers

You want a gateway built for MCP, with a server and tool directory, per-tool risk, and argument-level policy across all of them.

You want approval gates on actions

Destructive or sensitive tool calls wait for human sign-off, with every call recorded and attributable.

You are dev and platform led

You want to connect servers, write policy, and ship, without a services-led compliance engagement.

Choose DeepInspect when

Your risk is data leaving in prompts

Staff and apps paste PII, PHI, or PCI into LLMs, and you need detection and redaction on the prompt and response content itself.

You need regulated-industry compliance evidence

You want signed forensic records explicitly mapped to EU AI Act, HIPAA, 21 CFR Part 11, GLBA, or PCI DSS for auditors.

You want model cost routing

Routing simple calls to cheaper models, failover across providers, and per-actor token accounting at the model layer.

Using both

The surfaces are complementary. DeepInspect can govern what data leaves in a prompt to a model; PolicyLayer governs what an agent does with a tool call against your systems. A team with both prompt-content and tool-action risk can run them at their respective layers.

Put deterministic policy on every MCP tool call your agents make. Live in minutes.

Not just rules. A platform.

Whatever your agents touch, the same engine, audit, and access model is doing the work underneath every rule you write.

Deterministic engine

Rules run as code, not model judgement: argument-level conditions, quotas, deny-by-default. The same call gets the same decision every time.

Writing policies →

Separation of duties

Your security or compliance team writes and attaches policy without ever holding the upstream credentials or grant tokens.

Roles →

Tamper-proof audit

Every call is logged with its decision and the rule that fired, attributed to the identity, in an append-only record. Argument values are redacted, never stored.

Logs & security →

Credentials never reach the agent

Upstream secrets are encrypted at rest and injected by the gateway. The agent only ever holds a scoped token.

Logs & security →

Per-identity access

Every person and agent connects with its own scoped grant. Rotate or revoke any one of them instantly, without disrupting the rest.

Core concepts →

Live in minutes

Hosted gateway. Point your clients at it, register a server, issue a token. Nothing to install.

Quick start →

PolicyLayer and DeepInspect questions.

Is PolicyLayer a DLP tool?+

Not in the prompt-content sense. PolicyLayer can redact fields from tool results, but its focus is governing the MCP tool call itself: allowing, denying, rate-limiting, or gating the action against deterministic policy. DeepInspect focuses on detecting sensitive data in prompt and response content.

Do they govern the same traffic?+

No. DeepInspect sits on the path between users or apps and the LLM provider, inspecting prompts and responses. PolicyLayer sits on the path between agents and MCP servers, inspecting tool calls. Different traffic, different layer.

Which one do I need for agents taking actions?+

PolicyLayer. When an agent calls a tool to move money, change code, or alter infrastructure, PolicyLayer evaluates that specific call against your policy before it runs, with argument-level rules and approval gates.

Can I use both?+

Yes. They operate at different layers. Run DeepInspect on prompt-content risk to the model and PolicyLayer on tool-action risk through MCP servers.

Govern what agents do on every MCP call.

Deterministic, deny-by-default policy on every MCP tool call: approval gates, per-identity scopes, argument-level rules, and a tamper-proof audit log. Route your existing MCP servers through the gateway, live in minutes.

Instant setup, no code required.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.