Comparison · agent governance · Aegis Security

Aegis Security, measured.

Aegis finds AI agents passively and enforces policy on the calls routed through its proxy. This page scores that architecture against Agen.co on 14 capabilities, from eight Aegis sources, and prints the row Aegis wins and the three it ties.

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The short answer

  • Aegis discovers agents from five passive sources and enforces inline through an Envoy sidecar or an SDK decorator. An agent found by discovery but not routed through that enforcement point is inventoried, not governed.
  • Where it does enforce, the verdicts are real: allow, deny, sanitize or route for approval, at a published sub-200ms. Agen renders a verdict on every action, against any policy you write, in under 30ms.
  • Each call is checked against the requester and the agent together. The agent itself is documented as an inventory record built from fingerprints; no standing accountable owner per agent is documented. Agen gives every agent a named owner and attributes each action to them.
  • On a device, the documented enforcement point is the SDK inside agent code you own; the browser is a discovery source only. Agen enforces on the device, in the browser, at the gateway and in cloud and SaaS.
  • Aegis is stronger at the network layer, which we deliberately do not operate. Human approval, the per-action audit record and shadow-agent discovery score level with ours.
The long read

What Aegis actually governs.

Aegis pairs a wide passive discovery net with an Envoy sidecar and an SDK that sit in the path of a workload's outbound calls. That placement is what makes its enforcement precise, and what draws the line around which agents it reaches.

Discover, monitor, enforce

The product is presented as three stages over the same agent estate, and each one is worth scoring separately.

  • Discoverfive passive collection sources running at once: an eBPF sensor deployed to hosts, cloud connectors reading IAM and model-service activity, EDR integrations, a repository scan for agent SDK imports and MCP configuration, and SaaS audit logs for OAuth grants. Nothing has to self-register to be found.
  • Monitorper-agent behavioural baselines, anomaly detection and risk scoring over tool calls, API requests and data access, with signed traces exported to a SIEM.
  • Enforcea decision service returning allow, deny, sanitize or approval-needed, applied through an SDK decorator in the agent's code or an Envoy sidecar that intercepts its outbound calls and evaluates them against Open Policy Agent policy bundles.

Approved actions run on one-time, time-bound tokens rather than the agent's own standing credentials, so an agent does not carry lasting access to the systems it calls. That is a genuinely strong pattern.

Where Aegis is strongest

One of the fourteen rows below goes to Aegis and three are level. The row they win follows from a real architectural difference: the network path is a layer they build on and we deliberately do not.

  • Network-layer enforcementan Envoy sidecar beside each instrumented workload, evaluating every outbound call that crosses it, parameters included. We govern the action rather than the path, which is what lets one policy follow an agent onto the device and into the browser, and we run alongside whatever already sits in that path.
  • Shadow-agent discoveryfive passive sources, framework-agnostic, with no SDK or registration required to be found. Level with ours.
  • Human approval and the audit trailan approval verdict routed to a reviewer in Slack or Microsoft Teams, and a signed trace for every decision. Both are complete capabilities and both score level with ours.

Found is not the same as governed

Discovery and enforcement run on different mechanisms here. Discovery is passive and broad: it reads host telemetry, cloud logs, repositories and SaaS audit streams, so it reaches agents nobody declared. Enforcement is in-path: it needs the sidecar beside the workload or the decorator in its code before it can return a verdict.

The space between the two is where the runtime score comes from. An agent found on a laptop through an EDR feed, or in a SaaS tenant through an audit log, is visible and risk-scored, but unless it carries the SDK or routes through the proxy, no documented enforcement point on that device or in that browser stops its next action. Aegis describes its coverage as reaching developer endpoints; the mechanism documented there is the decorator, which governs agents whose code carries it.

Checked per call is not the same as owned

The identity check on each call is thoughtful. Aegis describes a dual-identity model in which access requires both the requester and the agent to be permitted, with traces carrying the agent identifier alongside the decision. For an interactive request, that resolves the action to a person.

The dependency is the requester. Aegis's own guidance recommends that every agent run under a workload identity bound to its owner. What its product documentation describes is narrower: the agent as an inventory record assembled from discovery fingerprints, with ownership verified during shadow-AI discovery, and no identity object carrying a standing accountable owner. An agent running on a schedule, or started by another system, has no requester to intersect with. A check tells you whether a call was allowed. An owner is who answers for it.

Three questions for a discover-then-proxy design

Aegis frames its product as discover, monitor, enforce. The table is organised around three narrower questions, each asking where that framework's reach ends.

  • Be at runtimeAegis returns a verdict on calls that cross its sidecar or carry its decorator. Does every agent its discovery finds get one, including the agents nobody instrumented?
  • Know the identityAegis intersects the requester with the agent on each call. Who answers for the agent when there is no requester — a scheduled job, or a call started by another system?
  • Cover everythingAegis discovers across hosts, endpoints, repositories, cloud and SaaS. Which of those surfaces also has an enforcement point, and are MCP tool calls governed off the proxied path?

Running it is the fourth group: Aegis lands one workflow lane in minutes and a first discovery report inside a week, with its sensors in your own cluster.

The scored comparison

Fourteen capabilities, scored side by side.

Runtime enforcement, identity and accountability, coverage, and what it takes to operate — each scored 0–5 on capability depth against vendor documentation, including the row Aegis wins and the three it ties.

Capability depthNoneCompleteAegisAgen.co
01 · Runtime enforcement
Verdict rendered at the moment of actionAegisInline where sidecar or SDK sitsCapable3/5Agen.coPer-action verdicts, <30msComplete5/5
Decision latency, published and measuredAegisSub-200ms ceiling, no method publishedStrong4/5Agen.co<30ms, published, no samplingComplete5/5
Human-in-the-loop approval on a risky actionAegisApproval verdict, Slack or TeamsComplete5/5Agen.coHuman-in-the-loop, built inComplete5/5
02 · Identity & accountability
Agent has a first-class identity objectAegisInventory record from fingerprintsPartial2/5Agen.coFirst-class agent identityComplete5/5
A named human accountable for each agentAegisOwnership checked at discoveryPartial2/5Agen.coNamed owner, every agentComplete5/5
Each individual action attributed to that humanAegisRequester and agent, per callCapable3/5Agen.coAttributed per actionComplete5/5
Audit record per actionAegisSigned traces, SIEM exportComplete5/5Agen.coA record per actionComplete5/5
03 · Coverage
Endpoint enforcementAegisSDK in own-built agents onlyPartial2/5Agen.coAgenShield on the deviceComplete5/5
Browser enforcementAegisSaaS audit logs, no extensionBasic1/5Agen.coBrowserShield, early accessCapable3/5
Network-layer enforcementAegisEnvoy sidecar, instrumented workloads onlyStrong4/5Agen.coNot our layer — works alongsidePartial2/5
Shadow-agent discoveryAegisFive passive sourcesComplete5/5Agen.coShadow AI surfacedComplete5/5
MCP tool governanceAegisMCP calls governed where proxiedCapable3/5Agen.coMCP tools governed per callComplete5/5
04 · Operate & buy
Time to first governed agentAegisMinutes per lane, week to inventoryStrong4/5Agen.coDays to a first governed agentComplete5/5
Deployment model and data residencyAegisIn-cluster sensors; self-hosting undocumentedStrong4/5Agen.coSaaS, hybrid, or on-premComplete5/5
10 rows Agen.co leads3 tied1 row Aegis leads
Levels reflect capability depth and supporting evidence. Capability descriptions based on vendor public documentation.
Get the walkthrough

Get the scored comparison walkthrough.

Thirty minutes, row by row, including the ones we lose to Aegis Security. You leave with the same table, scored for your environment. Tell us anything we should know in the comments.

length30 minutes
formatrow by row
commitmentnone
What the table shows

Two lines explain most of the gap: the sidecar and the requester.

Aegis's enforcement is real, and the scores say so: a 3 on runtime enforcement and a 4 on latency, with human approval, the audit record and shadow-agent discovery level with ours. Nothing about the proxy layer is weak.

The first line is the sidecar: an agent that Aegis discovered but nobody routed through the sidecar or SDK is inventoried and risk-scored, not stopped. The second is the requester: a call resolves to whoever asked, not to a standing owner of the agent. The cards below follow both lines through each group of the table.

Reading the table

Where Aegis's reach ends, group by group.

Each card takes one group of Aegis's scores and shows what it means for an agent already running against your systems.

01

Enforcement follows the sidecar

Allow, deny, sanitize and approval verdicts are genuinely inline, with parameter-level checks and a published latency. But a verdict needs the Envoy sidecar or the SDK decorator in place first, so an agent that discovery found and nobody instrumented is scored, not stopped.

enforcement pointsidecar or SDK
02

A permitted request is not an accountable owner

Every call is checked against the requester and the agent together, which scores a 3 and deserves it. But the agent is documented as an inventory record, with no named owner carried on it, so a scheduled or system-started agent has no human to resolve to.

standing owner per agentnone documented
03

Seen everywhere, governed where instrumented

Endpoints, browsers and SaaS tenants all feed discovery, which is broad and complete. Enforcement lives in the sidecar beside a workload or the SDK inside agent code, so a third-party agent on a laptop or in the browser is found rather than stopped. MCP configuration turns up in the repository scan, and MCP calls are governed where they cross the proxy.

browser enforcementnone documented
04

Fast per workflow, broad by the week

A single workflow lane deploys in minutes and the first discovery report lands inside a week with no code changes. Sensors run in your cluster and sensitive data is masked before telemetry leaves it; whether its policy and decision service can also be self-hosted is not documented.

first inventoryunder a week
Watch it happen

Every action resolved to the human who answers for it.

Not the request that started the work — a named accountable owner carried on every agent, and every individual action attributed back to them, including the agents that run with nobody watching.

agent ownership · live product scene
What closes the gap

Keep the proxy. Govern every agent you found.

Your network path keeps inspecting what crosses it. Agen governs on top: every agent you discover, not only the ones routed through a proxy; every action judged against your policy at the moment it happens on the device, in the browser, at the gateway and in the cloud; every verdict resolved to the human behind the agent.

Select a capability

Continuous discovery across your IdP, gateway, devices, cloud, and registries. Nothing has to self-register: agents are found, risk-scored, and resolved to a named human before they act.

  • Agentless and API-based across five surfaces
  • First-party, custom, and third-party agents alike
  • Every agent mapped to an owner, approver, and escalation
Agen Discover AI agent discovery flow: any identity provider, productivity suites and assistants, cloud, gateway, endpoints, and MCP server registries all feed one agent registry where every AI agent is inventoried, risk-scored on arrival, given a named human owner, and shadow AI is surfaced.
Discovery pulls from five surfaces into a single agent registry — no SDK self-registration required.
ClosesWhich agents are running that nobody registered?
no SDK required5 surfacesowner-mapped
Discover in depth →

Methodology

How these scores were reached.

Forty-two capabilities were considered against the ladder in our internal rubric; thirty-six were scored and fourteen are published here. Six were dropped and are not published on any page — pricing unit and platform cost because Aegis publishes no pricing, three more because its public documentation gave nothing to score either way, and one because our own score on it is still being confirmed with product. Three of the Aegis sources are technical articles that pair a product summary with a reference architecture; only the product summary is scored as shipped.

Sources8 primary
Evidence ledger
  1. Aegis Security — platform overviewTier ADiscover, Monitor and Enforce; five passive discovery sources (eBPF host sensor, cloud connectors, EDR integration, repository scan of agent SDK imports and MCP configuration, SaaS audit of OAuth grants); a decision service returning allow, deny, sanitize or approval-needed; signed audit with OpenTelemetry spans; enforcement through an SDK decorator and an Envoy sidecar forward proxy; sensitive data masked on the host before telemetry leaves the cluster; first discovery report in under a week with no code changes.
  2. Aegis Security — use casesTier AShadow-AI detection that verifies authorization and ownership across business units; in-flight redaction of sensitive identifiers; mapping of multi-agent communication paths; immutable, cryptographically signed traces exported to SIEM.
  3. Aegis Security — support and claimsTier AAction-level enforcement on refund and payment APIs with allow, block or require-approval decisions and parameter thresholds; one-time, time-bound signed tokens for approved actions; Slack and Microsoft Teams among the integrations; sub-200ms policy decisions; a single workflow deployable in under ten minutes.
  4. Aegis Security — IT and IAMTier ATime-bound, scoped access tokens with a 30-minute maximum lifetime; human approval for privileged actions; read and write boundaries on helpdesk agents; sub-200ms policy decisions.
  5. Aegis Security — finance and ERPTier AThreshold policies with dual approval and executive escalation before an agent moves money; Slack among the integrations; policies deployable across multiple regions.
  6. Aegis Security — agent permissionsTier AProduct summary: Aegis intercepts tool invocations at the network layer, evaluates payloads against OPA policy bundles and enforces dual-identity down-scoping of agent and requester permissions. The article also describes an Aegis-aligned reference architecture in which an Envoy-modelled proxy intercepts REST, gRPC, database and MCP traffic, traces carry agent identifiers and policy decisions, and each agent runs under a workload identity bound to its owner.
  7. Aegis Security — over-privileged agentsTier AProduct summary: Aegis intercepts tool calls at the data plane, evaluates them against OPA policy bundles and enforces ephemeral token exchange, described as covering AWS, Azure, SaaS and developer endpoints without code rewrites.
  8. Aegis Security — shadow AI agentsTier AAegis presented as continuous discovery, runtime control and zero-trust tool governance; the article's Aegis-aligned architecture routes MCP server requests through an inline proxy.

Vendor capabilities change. If a row is out of date or wrong, tell us and we will re-score it — corrections are published with the date they were made.

FAQ

Questions, answered.

What is Aegis Security?
It is a runtime security product for AI agents built around three stages. Discover finds agents passively from five sources: an eBPF host sensor, cloud connectors, EDR integrations, repository scans for agent SDKs and MCP configuration, and SaaS audit logs. Monitor baselines each agent's behaviour and scores risk. Enforce returns allow, deny, sanitize or approval-needed verdicts through an SDK decorator or an Envoy sidecar proxy, evaluated against Open Policy Agent policy.
Does Aegis block agent actions at runtime?
Yes, for the agents routed through its enforcement point. The sidecar or SDK intercepts each outbound call, evaluates it against policy including its parameters, and allows, blocks, sanitizes or holds it for approval, at a published sub-200ms. An agent found only by passive discovery, such as one on a laptop or in a SaaS tenant, is inventoried and risk-scored but has no enforcement point in front of its next action.
Can Agen.co run alongside Aegis?
Yes. Network-layer enforcement is a layer we deliberately do not operate, and it is the row on this page where Aegis scores above us. Agen governs the action rather than the path: every agent discovered agentlessly across five surfaces, every action judged against your policy in under 30ms on the device, in the browser, at the gateway and in the cloud, and every verdict resolved to a named accountable human. Nothing in your existing path has to be removed.
How does Aegis identify the human behind an agent?
By the request. Each call is permitted only when both the requester and the agent are allowed, which resolves an interactive request to a person and scores a 3. Aegis's guidance recommends binding each agent's workload identity to its owner; its product documentation describes the agent as an inventory record built from discovery fingerprints, with ownership verified during discovery, and documents no standing accountable owner. An agent running on a schedule or started by another system has no requester to resolve to.
Does Aegis govern MCP tools?
Where MCP calls cross its proxy, yes. Its repository scan finds MCP configuration, and Aegis describes its sidecar intercepting MCP messages alongside REST, gRPC and database traffic, evaluated against the same policy. An MCP call that never crosses the proxy, such as one to a local server over stdio, has no documented enforcement point. Agen governs every MCP tool call, across 1,000+ governed tools.
Where does Aegis score better than Agen.co?
One row of fourteen outright, and three more are level. Network-layer enforcement goes to Aegis: the product is built on an Envoy sidecar proxy beside each instrumented workload, a layer we run alongside rather than operate. Level with us on human-in-the-loop approval, on the per-action audit record, and on shadow-agent discovery.
How is Aegis priced?
Aegis does not publish pricing or a pricing unit, so this page leaves pricing unscored rather than guess. Agen is priced per governed agent with no prerequisite tier.
How current is this comparison?
The Aegis scores come from its own public pages — the platform overview, four use-case pages and three technical articles — and are re-checked against them on a fixed internal cadence. Where an article describes a reference architecture rather than the shipped product, this page says so instead of scoring it. All eight sources are listed on this page.

Bring your own comparison.

Send us the Aegis rows you would score differently. We will show you the Aegis page behind each score, and where we have read it wrong we will change the row.

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