Containment.AI runs one governance discipline across two tiers. The connected tier surface compared here is the data-layer control for autonomous agents: an HTTPS proxy in front of OpenAI, Anthropic, and Bedrock that inspects every prompt and completion and decides whether the regulated content inside the call is allowed to leave. (For the highest-assurance end, the same discipline is delivered in-path by the flagship High-Assurance Gateway.) Agent-runtime tools govern what an agent does; we govern what its actions carry. This page is an honest, side-by-side look at how that compares to a tool-layer governance toolkit — and why most teams shipping agents on regulated data want both layers.
Looking for the product, not the comparison? Start with Agent Governance. Last reviewed 2026-06-10; revised when a release changes the comparison.
Containment.AI is stronger on the data layer: a catalog of content-class detectors (HIPAA PHI, MNPI, ITAR/EAR, secrets, prompt injection, and more), real-time redaction so the agent keeps working while sensitive bytes are stripped, and a multi-LLM proxy with no agent-framework lock-in. The comparison case here, Microsoft's Agent Governance Toolkit (AGT), is stronger on the tool-call layer: zero-trust agent identity (SPIFFE / DIDs), OWASP Agentic Top 10 coverage, and execution sandboxing.
Neither product replaces the other. The honest pitch: if you ship autonomous agents on Azure Foundry, LangGraph, CrewAI, or the Microsoft Agent Framework, you probably want both — agent-runtime governance for behavior, and Containment.AI for the data crossing the LLM boundary.
AGT sits at the function-call boundary inside the agent process. Containment.AI sits at the HTTPS boundary to the LLM provider. They see different things and answer different questions.
@govern wrapper for Python, TS, .NET, Rust, Go)allow / deny / require_approvalallow / block / redact — agent keeps working, sensitive bytes don't leakNo marketing-speak. Where AGT is stronger, we say so. Where we are stronger, we say so. Where the gap is structural, we explain it.
| Capability | Microsoft AGT | Containment.AI |
|---|---|---|
| Architecture | In-process SDK / function wrapper | HTTPS proxy in front of LLM providers |
| Interception point | Tool / function calls; inter-agent messages | Every byte going to or from the LLM provider |
| Decision verbs | allow / deny / require_approval | allow / block / redact (substitute sensitive content with placeholder; agent keeps working) |
| Zero-trust agent identity (SPIFFE / DID / mTLS) | Yes — AGT's strength. | No (we identify humans and orgs, not agents) |
| Execution sandboxing / privilege rings | Yes — AGT's strength. | No |
| OWASP Agentic Top 10 mapping | 10/10 covered | Partial (prompt injection only; the rest are behavior classes that AGT is the right layer for) |
| PHI (HIPAA) detection | Not in shipped scope | Yes — dedicated detector |
| MNPI / insider-trading content detection | Not in shipped scope | Yes — dedicated detector |
| ITAR / EAR export-control detection | Not in shipped scope | Yes — dedicated detector |
| Secrets / API-key leakage detection | Not in shipped scope | Yes — dedicated detector |
| Prompt-injection detection | Yes (12-vector PromptDefense evaluator) | Yes (content-pattern + behavioral signals) |
| Shadow-AI discovery | Repo / process / config scanning | Actual API traffic observation (catches BYOK / personal-key bypass) |
| Multi-LLM provider coverage | LLM-agnostic at the tool layer (no provider-specific code) | LiteLLM-based — 100+ providers, no agent-framework lock-in |
| Tamper-evident audit log | Merkle-verified Decision BOM — AGT's strength. | Append-only audit_events; cryptographic chaining on the roadmap |
| Primary buyer | Developer / platform engineer | CISO / compliance / privacy officer |
| License / commercial | MIT, free; Microsoft-maintained (Azure pull-through) | Commercial SaaS or single-tenant deploy |
| AARM (CSA) conformance | Not yet claimed | Aligned with AARM v1.0 — see our AARM page for per-requirement status |
The clean architecture: AGT governs the agent's behavior inside its process; Containment.AI governs the data crossing the LLM boundary. A first-party AGT adapter — so a single policy decision can route through both layers — is on our roadmap; contact us if you want early access.
This page is researched, not generated. Primary sources behind every claim above:
We will revise this comparison as AGT releases new versions. If you spot an inaccuracy, email engineering@containment.ai and we'll fix it within one business day.
30-minute demo. We'll show the proxy intercepting a HIPAA-PHI paste in real time, alongside an AGT-style policy decision in the same flow.
Or email enterprise@containment.ai directly.