OOS Runs Everywhere
Cloud, data center, network, or edge device. Same codebase. Same behavior. Same reliability.
Most AI platforms are built for the cloud. They assume fast networks, powerful servers, and constant internet access. They work well in controlled environments.
But the real world is not a controlled environment.
Factories have limited connectivity. Remote sites have no internet. Vehicles, drones, and field equipment operate far from any data center. Medical devices need to respond instantly, regardless of network conditions. These environments need AI that works without depending on something else.
OOS runs in all of these environments. Not a different version. Not a limited version. The same OOS, the same codebase, the same defined behaviors, running wherever you need it.
Cloud, Data Center, Network, Edge
OOS is not an edge-only solution. It is not a cloud-only solution. It runs on any of these environments, and it runs the same way everywhere.
Deploy OOS in the cloud for large-scale operations. Run it in your data center for full control over your infrastructure. Place it on your local network for internal systems. Install it on an edge device for environments where connectivity is limited or unavailable.
Or use any combination. The deployment model is yours to decide. OOS adapts to your environment. Your environment does not need to adapt to OOS.
Cloud
Large-scale operations, elastic resources
Data Center
Full control, on-premise infrastructure
Local Network
Internal systems, corporate environments
Edge Device
Remote sites, constrained hardware, no internet
What Is an Edge Device?
An edge device is any computing hardware that operates close to where the work happens, outside of a traditional data center or cloud. These devices are often physically small, run on limited power, and may have no reliable network connection.
Single-Board Computer
As small as a phone
Drone Controller
Airborne, no fixed network
Industrial Gateway
Factory floor sensor hub
Medical Device
Patient monitoring unit
Vehicle System
Mobile, intermittent connectivity
Field Terminal
Remote site, no internet
Same Codebase, No Modifications
OOS does not have a "cloud version" and an "edge version." There is one codebase. It compiles and runs on different platforms and architectures. x86 server in a data center. ARM board the size of a phone on a factory floor. A machine running Linux, macOS, or Unix. The codebase is the same. The behavior is the same. The reliability is the same.
This means you do not need separate teams managing separate versions. You do not need to test one version for cloud and another for edge. What works in your data center works on the factory floor.
Works Without Internet
Many AI systems require an internet connection to function. They send requests to a cloud API and wait for a response. If the connection drops, the system stops.
OOS does not require internet access. When paired with a local AI model, OOS operates completely offline. The objects are defined locally. The behaviors are defined locally. The AI model runs locally. Nothing leaves the device. Nothing depends on an external service.
For environments where connectivity is unreliable or unavailable, this is not a feature. It is a requirement.
Small Footprint, Full Capability
OOS is designed to be efficient. It does not require powerful servers or large amounts of memory. It runs on modest hardware, including devices with limited resources.
But small does not mean simple. OOS is a full distributed system with reliable persistence that maintains data integrity even during power loss or system failure, authentication, and multi-threaded processing. Core capabilities remain available for edge deployment. The full system runs on constrained hardware because it was designed from the beginning to be efficient, not because features were cut.
This makes OOS practical for edge deployments where hardware is constrained. A sensor on a production line. A controller in a vehicle. A monitoring device in a remote location. OOS runs where large AI platforms cannot.
Combined with Unified Identity
When you deploy OOS across multiple environments, Unified Identity ties them together. An edge device on a factory floor, a server in the data center, and a cloud instance can all operate as one logical system. Same defined behaviors. Same consistent responses. The deployment is distributed. The identity is unified.
Add machines when you need capacity. Remove them when you do not. Move workloads between cloud and edge as conditions change. The identity holds. The behavior remains consistent.
Combined with Multi-Model AI
Different environments may call for different AI models. A powerful cloud model for complex analysis. A lightweight local model for an edge device. A specialized model for a specific task.
OOS supports this naturally. Each environment uses the model that makes sense for its hardware and connectivity. The defined behavior stays the same regardless of which model is behind it. A response from the edge device is consistent with a response from the cloud.
Why This Matters
Organizations do not operate in one environment. They have data centers and remote sites. Cloud infrastructure and factory floors. Office networks and field equipment. AI needs to work across all of them, consistently and reliably.
OOS was built for this. Not as an afterthought. Not as a compatibility layer. From the beginning, OOS was designed to run on any platform, any architecture, any environment, with or without internet, on hardware large or small.
Deploy it where you need it. It works the same everywhere.
OOS is not limited to the cloud. It runs on cloud, data center, network, and edge devices. Same codebase. Same behavior. Same reliability. Deploy it where you need it.