pLLMChat
Features of pLLMChat
Use Cases of pLLMChat
FAQ about pLLMChat
QWhat exactly is pLLMChat?
It’s an enterprise LLM gateway that unifies multiple model providers under one OpenAI-compatible endpoint and gives you governance, cost control and observability.
QWhich model providers are supported?
OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Llama, Cohere and any OpenAI-compatible endpoint—all through one uniform API.
QHow do I integrate it into an existing app?
Replace the OpenAI base URL with the pLLMChat endpoint; no further code changes are required.
QHow does pLLMChat handle security and compliance?
JWT validation, role-based access control (RBAC), full audit logs and Prometheus metrics provide enterprise-grade security governance.
QWhat performance can I expect?
Built in Go, the gateway sustains thousands of concurrent requests with minimal added latency.
QIs Kubernetes deployment supported?
Yes—packaged as cloud-native Helm charts with horizontal autoscaling and built-in observability.
QWhere can I find pricing?
Pricing is not listed on this page; please check the official documentation or repository for the latest details.
QWhat monitoring and cost-analysis features are included?
Prometheus metrics, budget alerts, intelligent caching and distributed rate-limiting give you real-time governance of cost and usage.
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