Comparison · Strix vs Open Policy Agent (OPA)
Strix vs Open Policy Agent: general-purpose engine vs opinionated kernel.
OPA is a Cloud Native Computing Foundation graduate project — a general-purpose policy engine you embed wherever you need policy decisions. Strix is an opinionated execution-control kernel for AI systems with built-in three-state decisions, single-use execution tokens, cryptographic evidence, and a runtime kill switch. OPA gives you a policy primitive; Strix gives you an enforcement product.
Answers the question: “Should I use OPA or Strix to govern AI execution?”
Execution control for AI systems
Intercept, evaluate, sign every state-changing action.
General-purpose policy engine for cloud-native authorization
The bottom line
Both products exist for a reason. Here's when each is the right call.
- You're governing AI agents and need three-state decisions (ALLOW/DENY/INTERCEPT) out of the box, not as something you build.
- You need cryptographically signed evidence with a public JWKS — not a policy decision returned as JSON.
- You need single-use, revocable execution tokens for human-in-the-loop approval.
- Your auditor wants third-party verifiable evidence and a stable canonical schema.
- You'd rather buy execution control than build it on top of a policy engine.
- You need a general-purpose policy engine across many domains (Kubernetes admission, Envoy, Terraform, application authz) — not just AI.
- Your team is comfortable writing Rego and prefers building authorization primitives in-house.
- You're already running OPA in your stack and adding AI authz is a small extension.
- You don't need cryptographic evidence — application-level audit logs are enough.
- You want a CNCF-graduated, vendor-neutral OSS project as a foundational building block.
Feature-by-feature
Each row is a specific capability. We've tried to be honest — there are categories where the other side wins.
| Capability | Strix | Open Policy Agent (OPA) |
|---|---|---|
Product shape | Opinionated execution-control kernel for AI systems | General-purpose policy engine (Rego language) |
Governance scope | Capability registry + policy + tokens + evidence (vertically integrated) | Policy decisions; you build the rest |
Three-state decisions | ALLOW / DENY / INTERCEPT built in; INTERCEPT triggers human approval | Decisions are typically allow/deny; multi-state requires custom orchestration |
Single-use execution tokens | HMAC-signed, atomic redemption, revocable, 5-min default TTL | Not part of OPA scope — you build this layer yourself |
Cryptographically signed evidence | Ed25519 signatures, public JWKS, third-party verifiable | Decision logs available; signing is a custom integration |
Public verification API | /api/public/verify is unauthenticated, rate-limited, public | Decision logs flow to OPA's decision-log service or your sink |
Policy authoring | Risk-tier-based policy in TypeScript with versioned rule sets (content-addressable) | Rego — declarative, expressive, mature ecosystem |
Domain breadth | Application-layer execution control for AI systems | Kubernetes admission, Envoy, Terraform, microservice authz, etc. |
Open source | Source available at github.com/Strixgov/strix; not a CNCF project | CNCF graduated; Apache 2.0; vendor-neutral |
Time to first governed action | One function call: strix.govern({ capability, actor, context }) | Write Rego, deploy OPA, integrate decision API, build evidence pipeline |
Built-in capability registry | Yes — risk-tiered, queryable, exposed at /api/v1/capabilities | You define data sources; OPA evaluates against them |
Runtime kill switch | Token revocation propagates to in-flight executions; redemption is atomic | Possible to build, not part of the product |
Tenant isolation | Postgres RLS at the database with app.current_tenant_id | Application-layer responsibility; OPA is tenant-agnostic |
Compliance mapping | EU AI Act, NIST AI RMF, SOC 2 mapped end-to-end | OPA itself is policy-engine-agnostic; mapping is your responsibility |
Extensibility | Capability registry + policy versioning; opinionated path | Highly extensible — Rego can express almost any policy logic |
Ecosystem | Newer; @strixgov/* npm packages; Academy SDK; tool-gateway | Massive — Gatekeeper, Conftest, Styra DAS, hundreds of integrations |
When to use which
Concrete scenarios. If your situation looks like one of these, the recommendation should be obvious.
We need policy across Kubernetes admission, Terraform plans, and microservice authorization.
OPA is purpose-built for cross-domain policy. Strix is application-layer AI execution control — wrong tool for Kubernetes admission.
We're governing autonomous AI agents and need signed evidence + three-state decisions + execution tokens.
Strix is an integrated product for this exact problem. Building it on OPA means writing Rego for the policy, building token issuance + atomic redemption, building the signing pipeline, building the JWKS endpoint, building the public verifier — easily 6-9 months of work to reach feature parity.
Our security team has standardized on OPA and we have a Rego playbook for everything.
Stay on OPA if standardization matters more than the time-to-value Strix offers. You can build AI execution control on top of OPA — it just takes longer and the auditor-grade evidence layer is yours to build.
We're a federal contractor and our auditor wants third-party verifiable cryptographic evidence.
OPA decision logs are application-attested unless you bolt on a signing pipeline. Strix ships with Ed25519 signatures + public JWKS + open-source verifier. The math is in the box.
We have OPA for cluster + microservice policy and need AI execution control on top.
Run them at different layers. OPA continues handling cluster + service authz. Strix handles application-layer AI execution governance. Each is best at what it's designed for.
Our timeline is 'production in 6 weeks' and we need governance for AI tool calls.
Strix integration is a single function call per tool. OPA-based execution control with equivalent evidence guarantees is a multi-quarter build.
Common questions
Why not just write Rego and use OPA?+
You can. The question is what you're optimizing for. OPA gives you a policy decision; you still need to build the capability registry, the token issuance, the atomic redemption, the human approval flow, the signing pipeline, the JWKS endpoint, the public verifier, the canonical evidence schema, and the cross-runtime byte-parity tests. Strix is what you get if you assemble all of that into a product. If your team values 'we built it ourselves on OPA' more than time-to-value, that's a legitimate choice.
Does Strix use OPA under the hood?+
No. Strix's kernel is a deterministic, content-addressable evaluator written in TypeScript. The decision is computed in-process with zero network dependency. We considered OPA early on; the deterministic content-addressable version-hash invariant and the canonical signed-evidence schema fit better with an in-process evaluator than with a sidecar policy server.
Can OPA produce signed evidence?+
Not natively. You'd implement a signing layer on top of OPA decision logs. The signing primitives are well-known (Ed25519, JWKS, RFC 7517) — it's a real engineering effort but not novel. Strix's value is that this layer is built, tested, version-locked (canonical 13-field payload), and externally verifiable out of the box.
Is Strix going to add Rego support?+
Not on the current roadmap. Strix policy is intentionally narrower than Rego — it's domain-specific to capability + risk + actor + intent + context, with deterministic content-addressable hashing. The narrower surface is what makes the canonical evidence schema possible. Adding Rego would either fork the schema or require canonical-form serialization of arbitrary Rego — neither is on the roadmap.
What about Styra DAS?+
Styra DAS is a managed control plane for OPA — adds policy authoring, distribution, and decision-log management to OPA's engine. It's a different layer than Strix; if you're committed to OPA at runtime, Styra DAS is the management layer. If you want execution-control + signed evidence + tokens as a product, Strix is more direct. We can produce a Strix vs Styra DAS comparison if useful for your evaluation.
Production governance. Zero bypasses. One evidence trail.
Strix is running in production today — 127 capabilities defined, every decision recorded. See the governance kernel in action in 15 minutes.
Currently in private beta — limited spots available.
npx @strixgov/verifier@latest 5686