Spend Limits
Set project-level and API-key-level limits that govern LLM usage automatically at the gateway, helping teams avoid runaway costs, unauthorized access, and surprise provider bills.
Keep LLM budgets predictable with gateway-enforced spend limits, real-time alerts, and usage visibility across every model and provider. FastRouter helps engineering, platform, and finance teams prevent surprise AI bills, catch abnormal usage early, and control access by project or API key without slowing product development or adding custom cost-control logic to every application.
Control LLM budgets with limits, alerts, analytics, billing visibility, and governance across every provider.
Set project-level and API-key-level limits that govern LLM usage automatically at the gateway, helping teams avoid runaway costs, unauthorized access, and surprise provider bills.
Receive real-time notifications when cost, latency, errors, provider failures, or usage anomalies exceed your configured thresholds across any connected model or provider.
Track token usage, request volume, and AI spend by model, provider, project, and team from one unified dashboard built for operational visibility.
Reduce unnecessary premium-model usage with intelligent routing, batch processing, and automated model selection that balances cost, quality, latency, and throughput.
Unify spend across OpenAI, Anthropic, Google Gemini, xAI Grok, and other providers into one source of truth for reconciliation and reporting.
Control who can use which models, assign member roles, restrict sensitive access, and enforce policy consistently across applications through the gateway.
FastRouter turns LLM cost management into an operational control layer instead of a monthly surprise. Teams can cap spend by project or API key, receive real-time alerts when usage changes, and analyze consumption across providers from one dashboard. Combined with governance, routing, and consolidated billing, it gives engineering and finance shared visibility without slowing production AI delivery.
See how production AI teams can reduce cost risk while keeping model access flexible and reliable.
"Amazing product. Have had a great experience using FastRouter. Reliable access to models across providers helps removes the worry about outages or vendor lock-in."
FastRouter brings cost visibility, alerts, and policy enforcement into one LLMOps control plane.
Gateway-enforced caps apply across applications, helping teams prevent unplanned LLM cost spikes.
Alerts surface budget, latency, and error issues instantly from one provider-agnostic dashboard.
Unified billing and analytics connect every model request to teams, projects, and providers.
Role-based controls restrict expensive models and sensitive access without slowing product teams.
A platform team focused on reliable AI operations.
FastRouter is an LLMOps platform built for organizations running AI in production across many models, providers, and teams. Its vision is to give engineering, platform, product, and finance teams one OpenAI-compatible control plane for reliable model access, cost governance, observability, guardrails, evaluations, and routing. Rather than forcing teams to maintain separate provider integrations, dashboards, invoices, and policy logic, FastRouter centralizes operational control at the gateway. That approach helps teams move quickly while keeping AI usage accountable, measurable, and resilient. For companies scaling generative AI, FastRouter provides the foundation to manage spend, monitor performance, and enforce responsible access without slowing experimentation or deployment.
LLM spend limits are budget guardrails that cap or control AI usage before costs exceed planned thresholds. In FastRouter, limits can be applied at the project and API-key level, so teams can separate budgets by application, environment, or user group. Because limits are enforced at the gateway, policies apply consistently across every connected model and provider.
Get practical guidance on limits, alerts, and AI cost governance.
Developer-friendly integration through one familiar API.
Centralized controls for responsible AI usage.
Operational visibility across production AI workloads.
Tell us how your team uses LLMs today, and we’ll help you identify the right budget limits, alert thresholds, and governance setup for predictable AI spend.
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