Keep AI uptime and costs controlled
LLM gateway for production-ready AI
Universal endpoint
Model routing
Credential management
Cost control
Full visibility
Prompt security
Run reliable AI apps
Uptime that doesn’t depend on any one provider.
- Routing: Switch to a backup model if a provider fails or hits rate limits without code changes.
- Health checks: Pull degraded providers from rotation in real time and reinstate them when they recover.
- Circuit breaking: Stop sending traffic to failing providers before errors cascade.
Protect provider keys
Create virtual keys and manage changes from one place.
- Issue per app or agent: Generate a virtual key for every team, app, or agent that needs model access.
- Rotate without code changes: Cycle, revoke, or update keys from the gateway without changing code.
- Monitor and control usage: Track every call made with every key, and revoke access the moment it’s no longer needed.
Control AI costs
Predictable AI spend, no surprise overages.
- Per-team, per-user, per-model budgets: Set independent spend caps that match how teams operate.
- Rate limiting: Throttle by request count and traffic volume to prevent runaway scripts.
- Budget enforcement: Enforce limits at the gateway and avoid surprise invoices.
Monitor AI traffic
Track model performance, routing, and spend.
- Real-time dashboard: Track every call by latency, tokens, model, and status in one view.
- Audit history: See routing decisions and error codes call by call.
- Log streaming and export: Pipe activity into your existing audit and observability stack.
Built for enterprise environments
SaaS
Fully managed deployment for fast setup and ongoing updates.
Private Cloud
Deployed in your cloud environment to meet security and compliance requirements.
On-Prem
Run entirely within your infrastructure for maximum control and data residency.
Frequently asked questions
What is an LLM gateway?
An LLM gateway is a control layer between your applications and AI model providers that centralizes routing, credential management, and data protection. Barndoor’s LLM gateway gives IT and security teams policy enforcement and visibility across every AI request — regardless of which model or provider your teams are using.
How is an LLM gateway different from an API gateway?
API gateways route general web traffic between services. LLM gateways are purpose-built for AI — handling token budgets, streaming, prompt inspection, and multi-model routing. Barndoor extends this further by pairing LLM gateway governance with MCP controls, covering both the models your teams call and the tools AI agents access.
Why do enterprises need an LLM gateway?
Without a gateway, every team connects directly to AI providers using scattered API keys with no cost controls, no data visibility, and no way to enforce security policies. Barndoor centralizes that control — giving IT one place to set spend limits, rotate credentials, and block sensitive data from leaving the environment.
How does an LLM gateway protect sensitive data?
It inspects prompts and responses inline — before traffic reaches a model provider — and applies DLP policies that block or redact PII, credentials, and regulated content. Barndoor enforces these policies across every provider your teams use, so data protection doesn’t depend on individual developers following the right steps.
How does an LLM gateway govern AI agents?
AI agents call language models to reason, and that traffic carries the same data and cost risks as any other AI request. Barndoor governs both layers of agentic AI: the MCP layer controlling which tools and data sources agents can access, and the LLM gateway layer governing which models they call.