OpenLeash Cloud vs Private Cloud: how to choose agent security architecture
Some teams want agent supervision without running infrastructure. Others need source code, prompts, approvals, identity, and logs inside their own cloud. The product has to respect both.
OpenLeash keeps the governance model consistent while letting teams choose hosted OpenLeash Cloud or customer-controlled Private Cloud.
The architecture decision is really a trust-boundary decision
AI agent security is not only about which model you use. It is about where code, prompts, logs, approvals, identities, plugin signals, and audit records travel. A small team may be perfectly comfortable with a hosted control plane. A regulated organization may need the same control plane inside its own cloud.
That difference should not split the product into two unrelated worlds. The risky behaviors are the same: destructive commands, sensitive context, privileged tools, prompt injection, dependency changes, expensive model loops, and approvals that need to be remembered later.
The architecture question is where those decisions are evaluated and stored.
Indie devs should not need a platform team
A solo developer wants the shortest path from install to protection. They should be able to install the desktop client, connect their agent workflow, and get lightweight checks around risky actions without learning a dashboard meant for a Fortune 500 rollout.
That is the job of OpenLeash Cloud for personal usage: make AI coding agent security feel like a useful default, not a new infrastructure project. Solo users can use OpenLeash Cloud with OpenLeash-managed evaluation or bring their own LLM provider key. They should manage their personal account from the desktop client and account pages, not an organization dashboard.
The product should feel like a seatbelt, not a compliance program that accidentally landed on a side project.
Organizations need control over the trust boundary
A security team may have a very different requirement. Source code, prompts, audit logs, user identity, policy state, approval decisions, and evaluation behavior may need to stay in a customer-controlled environment. That is not paranoia. That is how regulated infrastructure works.
Private Cloud is for that world. Desktop and mobile clients talk to a customer-hosted client API. Admins use customer-hosted dashboard services. Identity, policy, audit, users, approvals, and evaluation can be managed centrally by the customer.
This matters for CISOs because agent governance touches several existing control areas at once: endpoint behavior, data loss prevention, identity, developer tooling, source-code access, cloud privilege, logging, and incident response.
The product semantics should not change
A hosted product and a self-hosted product drift when the SaaS version secretly becomes the real product. OpenLeash tries to avoid that by keeping the public core meaningful: hooks, policy interfaces, approvals, audit, client APIs, dashboard APIs, and the extension model.
OpenLeash-operated SaaS adapters can handle hosted tenancy, billing, production credentials, abuse controls, and cloud operations. They should not redefine what an approval means or how agent governance works.
That is especially important for teams that start in OpenLeash Cloud and later need Private Cloud, or teams that evaluate Private Cloud but still want the same developer experience their smaller teams saw in the hosted product.
Choose based on operational reality
Choose OpenLeash Cloud when speed matters, the team is small, hosted management is acceptable, and you want a fast path to consistent agent approvals, masking, audit, and policy. That may fit an indie developer, a startup, or an organization that wants governance without operating the backend itself.
Choose Private Cloud when the trust boundary, identity provider, data residency, audit retention, internal network access, regulatory posture, or operating model requires customer control. Private Cloud is also the right answer when the organization wants agent governance to live beside existing security infrastructure.
The important thing is that both paths supervise the same risky agent behaviors. The deployment mode changes who operates the backend. It should not change the meaning of safe agent work.