An infrastructure control plane for your coding agents.

Temperature zero reduces variance. It does not make a model honour a constraint you wrote in a prompt, and it does not survive a model upgrade. The determinism you need isn't in the sampler - it's in what happens after the model decides. Qovery moves the operations out of the model: the agent expresses intent, procedural code performs it.

Every other approach either decides whether an action is allowed without performing it, or wraps a tool whose output is unbounded. A finite catalog of maintained operations is the only shape where verification gets cheap enough for an agent to act unattended. Qovery has been operating production for 200+ companies in regulated industries for five years - the deterministic execution layer agents need existed before the agents did.

A prompt is a request, not a boundary. And an LLM guardrail or judge agent is a nondeterministic check on a nondeterministic actor - you are still the guardrail.

Two different gaps. PR approval runs into automation bias - when the agent is right most of the time, approval becomes reflex. And GitOps only governs what is in Git: no provisioning, no teardown, no drift, no rotation. Policy assertions on terraform plan bound an infinite space by enumerating its bad parts, forever; plan also checks your code, not what is deployed, so drift passes policy and still breaks production.

IAM answers whether an identity may call an endpoint. Qovery answers whether a specific operation, with these parameters, on this resource, in this environment is permitted - then performs it as procedural code. An IAM policy can let an agent scale a service. It can't stop the agent scaling it to zero at 3am.

Every action records which agent, for which person, in which session, along with the diff, the policy result and the rollback path - a service account in CloudTrail does not answer an auditor. Agents also inherit your existing RBAC, so there is no parallel access model to maintain. And every framework you're certified against - ISO 9001, SOC 2, DORA, HDS - asks whether your processes are defined, repeatable, auditable and improvable; a process whose outputs can't be reproduced makes that harder to demonstrate, not easier.

Authorization platforms decide whether. They never execute, so nothing is atomic, reversible or repeatable. Durable execution engines give you the guarantees as primitives - you still write and maintain every operation yourself.

That is the quarter. The forever is the policy engine, audit, rollback, drift, secrets lifecycle, and a catalog tracking every provider change. The same applies to AI SRE tools: they compress time-to-understand, but remediation needs authority over infrastructure - a catalog problem.

Both. Qovery operates on a split-plane architecture: the Qovery Control Plane manages orchestration via secure APIs, while the Data Plane (your Kubernetes clusters, VPCs, apps, and databases) can live wherever you need it. You can bring your own cloud account (AWS, GCP, Azure, Scaleway, and more) via BYOK (Bring Your Own Kubernetes), or let Qovery manage the cloud infrastructure for you. Either way, you retain full ownership of your data and underlying resources.

No. Because Qovery provisions industry-standard infrastructure using Terraform and native Kubernetes manifests on your own cloud account, you retain full ownership. If you ever stop using Qovery, your infrastructure keeps running natively on your cloud. You can take over the generated configurations without rebuilding your stack from scratch.