Kanishkraj Singh Chauhan

A year ago, an AI/LLM Gateway felt like a thin layer: auth + simple routing across a few model providers. That era s over. As teams ship agentic apps with many moving parts (models, tools via MCP, prompts, guardrails) the complex problems are now control, standardization, and observability.

What a modern gateway really does:

• Unified interface & routing: Swap models/providers without code changes; policy-based routing (latency/cost/quality), failover.

• Centralized access & governance: One place for keys, RBAC, per-team quotas, audit logs, and data residency.

• Guardrails at the edge: PII redaction, safety/moderation, jailbreak & prompt-injection checks, tool permissioning.

• Experimentation & evals: Prompt/version management, playgrounds to connect models + MCPs and build agents

• Deep observability: Traces for prompts/responses/tools, tokens/cost, latency SLOs, drift signals; caching/rate-limits/batching.