AUTHORIZATION FOR USERS, SERVICES & AI AGENTS
Untangle your permissions.
Replace scattered permission checks with one policy layer — enforced beside your application, audited from one place.
SUB-10MS DESIGN TARGET · EVERY DECISION LOGGED
Every service checks permissions its own way. That's the tangle.
The same rule gets re-implemented in every codebase — each copy slightly different, drifting further with every release, until no one can say what the system actually allows. ZStrike pulls those checks out of your code and into policies: written once, enforced beside every service, logged with every answer.
The plan, running. Every decision, one screen.
Authorize locally. Govern centrally.
Today authorization lives in scattered ifs, or a central service a network hop away. ZStrike runs it beside your code, governed in one place.
Impact analysis on every change
A semantic diff proves when a draft can disagree with the live policy; a replay shows which recent decisions would flip. The blast radius, before you merge.
Sub-10ms decisions
Zero network hops: your service calls a sidecar on localhost, policies already in memory — built to answer allow or deny in under 10ms.
Zero single points of failure
Distributed sidecars keep deciding on last-synced policy when the control plane disconnects — no remote dependency in the request path.
Context-aware access
Decisions use real-time application state — user attributes, resource tags, environment — for every caller, human or AI agent, down to the row, field, and action.
Guardrails for AI agents
An agent is a principal like any other: scoped identity, hard caps, no self-escalation. Every call it makes is checked in real time and lands on the record.
Why was that allowed? Traced, with proof.
An AI agent pushes a $480K refund; ZStrike denies it in a millisecond. The record doesn't just say no — it names the rule that fired, the version it ran under, and the context it saw. The why ships with every answer, for every caller, human or agent.
And the trail doesn't rot when rules change. This record pins v6 even after v7 ships — so who changed what, when, and why an action was denied stays provable months later.
WHO · WHAT · WHEN · WHY — WITH PROOF
const decision = await zstrike.check({ principal: 'User::"r.patel"', action: 'Action::"refund.approve"', resource: 'Order::"ord_8841"', context: { amount: 4200 }, }); // → DENY · exceeds approval_limit (2500)
Enforce anywhere. One call.
Drop the SDK into any service — or in front of any AI agent. Every check is one local call: allow or deny, with the reason.
ZSTRIKE AUTHORIZES ZSTRIKE — EVERY ADMIN ACTION PASSES THROUGH THE SAME ENGINE WE SHIP
Free while we build together.
The cloud is in beta — free now, and beta teams keep early-access pricing at launch. BECOME A DESIGN PARTNER →
Managed control plane. Early-access pricing locked in when we launch.
For teams with compliance and scale requirements.
Questions, answered.
Does ZStrike replace my identity provider?
No — ZStrike governs authorization, not authentication. Your IdP still answers who someone is; ZStrike decides what they can do. Identities, groups, and attributes sync in from the provider you already run.
How is this different from roles in my database?
Roles tables answer "who has a role" — not "can this user take this action on this resource right now." ZStrike evaluates relationships, attributes, and context in one place, so permission logic stays out of your queries.
Where does authorization data live?
ZStrike stores only the relationship metadata you sync — never row contents. Deployments are region-pinned, and self-hosted engines are available on enterprise plans.
Can it govern AI agents and automations?
Yes — agents get scoped identities with hard limits (spending caps, read-only scopes, no self-escalation), checked on every call and logged like any employee. Policies themselves can be drafted from plain English by AI, then checked against the description before they save.
Can I start with one service?
Yes — that’s the usual path. Put the sidecar beside one service, model its checks in Cedar, and expand service by service. Nothing requires a big-bang migration.
Do I need Kubernetes?
No. The decision engine is a container that runs beside your service — a sidecar is the common shape, but any environment that can run a container next to your app works.
How do I migrate existing permission checks?
One check at a time. Model the rule in Cedar, add the SDK call beside the existing logic, and delete the old branch once the two agree. Start with your gnarliest check — that’s the one that pays for the move.
What stops a policy change from breaking production?
Impact analysis. Every draft is checked against the live version — a semantic diff proves where they can disagree, and a replay of your recent decisions shows exactly which ones would flip, in which direction. You see the blast radius before you merge, not in an incident.
How long does an initial integration take?
The mechanical part is small: deploy the sidecar, add one SDK call. The real work is modeling your policies, and that depends on how tangled they are today — scoping it is exactly what an engineering briefing is for.
What happens if ZStrike is unavailable?
Decisions don’t stop. The sidecar keeps answering from last-synced policy and entity state, because the control plane is never in the request path. Fail modes are configurable per resource.
Bring us your gnarliest permission check.
Thirty minutes with the engineers building ZStrike: bring one or two real cases, and we model them in Cedar, live. We read every message and reply within one business day.
OR EMAIL HELLO@ZSTRIKEHQ.COM