> ## Documentation Index > Fetch the complete documentation index at: https://docs.subconscious.dev/llms.txt > Use this file to discover all available pages before exploring further. # FAQ > Common questions about the Subconscious Inference System ## Why use this over Claude Code or Codex? Closed hosted tools can send prompts, code, and engineering context outside your trust boundary. The Subconscious Inference System gives your team frontier-level coding-agent intelligence while keeping API Gateway traffic, Inference Runtime execution, and deployment policy inside infrastructure you control. See [Compliance](/on-prem/trust-center/compliance) for the data and IP boundary. ## Why use Subconscious instead of hosting the models and managing GPUs ourselves? You can rent GPUs and host open models yourself, but the hard part is serving coding-agent workloads efficiently and reliably. Subconscious helps manage the API Gateway, Inference Runtime, Distribution Platform, admin surfaces, upgrades, and support. The Subconscious Inference System is designed to serve teams of engineers with roughly half the GPUs compared with off-the-shelf inference runtimes like vLLM. See [How it works](/on-prem/how-it-works) and [Configurations](/on-prem/deployments/configurations). ## How does this fit into our security and compliance review? The customer-hosted deployment is designed to fit into customer-controlled security, compliance, and change-management processes. The API Gateway and Inference Runtime run in your cloud account or controlled environment, and you retain control over deployment, access, monitoring, networking, data, and change management. See [Compliance](/on-prem/trust-center/compliance). ## Where does the Subconscious Inference System run? The API Gateway and Inference Runtime run in the customer's cloud or controlled infrastructure. Depending on your configuration, Inference Runtime GPU workers may run in the same cloud, another customer-controlled environment, or a specialized GPU provider behind the API Gateway. See [How it works](/on-prem/how-it-works) and [Configurations](/on-prem/deployments/configurations). ## What data does Subconscious access? By default, production prompts, completions, source code, API keys, API Gateway logs, Inference Runtime logs, and operational data should remain in the customer environment. Customers may choose to share selected logs, screenshots, metrics, or traces for support. See [Compliance](/on-prem/trust-center/compliance). ## How are upgrades and patches delivered? The Distribution Platform delivers releases, patches, and release metadata. Customers can approve updates through their own change-management process or choose an assisted update workflow. See [Distribution Platform](/on-prem/distribution-platform/overview) and [Customer success](/on-prem/integration-journey/customer-success). ## Can we control when updates are deployed? Yes. Production updates are intended to be customer-approved and deployed according to your policy, maintenance windows, and change-management requirements. See [Methods](/on-prem/deployments/methods) and [Compliance](/on-prem/trust-center/compliance). ## Do you support vulnerability scanning? Subconscious can provide or work toward providing release evidence such as vulnerability scan results, SBOMs, image digests, checksums, and release notes. Customers can also scan release artifacts and deployed components with their own tools. See [Compliance](/on-prem/trust-center/compliance) and [Distribution Platform](/on-prem/distribution-platform/overview). ## What clouds and Kubernetes environments are supported? The deployment can be planned for AWS, GCP, Azure, NeoCloud or dedicated GPU providers, and customer-controlled Kubernetes environments. Exact support depends on your cloud, networking, GPU placement, registry, and security requirements. See [Configurations](/on-prem/deployments/configurations). ## Do we need to bring our own GPUs? Not always. Customers can provide approved GPU capacity, use cloud GPU resources, or route through specialized GPU providers depending on the deployment design. We can also help you source GPU capacity through our network of partnerships. See [Configurations](/on-prem/deployments/configurations). ## If a new model comes out, can we deploy it? Yes, as long as the model architecture is supported by the Inference Runtime and enough GPU capacity is available. If existing capacity is already allocated, we may need to add GPU resources or replace an existing route before deploying the new model. See [Customer success](/on-prem/integration-journey/customer-success). ## Which coding agents are supported? The API Gateway exposes OpenAI- and Anthropic-compatible endpoints, so teams can connect common coding agents (Claude Code, Cursor, Codex, OpenCode, Pi, etc.) and internal tools that support those API shapes. See [API Gateway setup](/on-prem/api-gateway/setup). ## What happens if the deployment has an incident? The customer owns incident response for the API Gateway and Inference Runtime in its environment. Subconscious supports investigation and remediation when requested by the customer, using customer-approved access or diagnostic sharing. See [Customer success](/on-prem/integration-journey/customer-success) and [Compliance](/on-prem/trust-center/compliance).