IonSignal builds Qiln, the reversible runtime layer for agent-safe AI workflow capsules.

A production AI workflow system is more than source code. It combines models, assets, custom dependencies, scripts, microservices, persistent storage, API routes, scoped credentials, golden tests, and external system calls.

Once that system powers a product, customer deliverable, revenue-producing workflow, or internal operation, even a small change can break a known-good release.

The Safe Release Path
Qiln captures the deployable system as a versioned capsule and gives every change a controlled release loop:

Snapshot a known-good capsule
└── Fork a branch
    └── Make changes (human or AI agent)
        └── Run golden tests
            └── Inspect capsule diffs & side-effect logs
                └── Approve promotion
                    └── Roll back when needed

Agent Safety & Control
Humans and AI agents work in isolated forks rather than editing production directly.
Branch policies can block, log, mock, or approval-gate external calls during testing. Production secret references are never exposed to agent branches, and production routes move only after authorized approval.
Agents get forks, not production.

Get Started
Qiln is built for commercial teams operating interconnected, model-backed AI workflow systems where preserving a working system and safely evolving it matters more than generic hosting or disposable development environments.
Bring us the production AI workflow system you are afraid to change, upgrade, move, or let an agent modify. We will help turn it into a capsule and prove the fork → test → diff → promote/rollback path on a real change.

Delivery Models
• Qiln Managed — Managed AI workflow capsules operated by IonSignal
• Qiln Community — Open-source, self-managed Qiln for owned GPU servers
• Qiln Appliance — Private Qiln deployments on customer-owned hardware
IonSignal, Inc. was founded in 2025 and is headquartered in San Francisco.

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