The Only On-Prem AI Control Plane: Why SmartFlow 1.3 Changes the Enterprise AI Landscape
SmartFlow 1.3 delivers 12 new capabilities spanning LLM, MCP, and A2A governance — the only platform covering all three, deployable on-premise.
For the past four months, we have written about the enterprise AI governance challenges that defined late 2025 and early 2026: the shadow AI data security crisis, the MCP governance gap, the A2A agent communication blind spot, the regulatory compliance clock, and the persistent inability of most organizations to prove their governance to auditors and regulators.
Today, we are announcing SmartFlow 1.3 — 12 new capabilities that directly address these challenges across every enterprise AI integration pattern.
SmartFlow has always been an enterprise AI control plane: a network-layer proxy that intercepts, governs, and optimizes AI traffic without requiring code changes in existing applications. With 1.3, the platform now covers all three ways enterprises interact with AI: direct LLM calls, MCP tool orchestration, and agent-to-agent communication via the Google A2A open protocol.
The MCP Gateway now supports every transport protocol (HTTP, SSE, STDIO), every authentication model (API keys, OAuth client credentials, OAuth PKCE for user consent, Basic Auth, mTLS), and enterprise access controls through AD/LDAP group-based allow/deny with approval workflows. Semantic tool search lets agents discover capabilities in plain language across every registered server. MCP tool-call caching prevents redundant invocations.
The A2A Agent Gateway implements the full Google A2A open protocol — Agent Cards, task lifecycle management, SSE streaming, Redis-backed task history, and cross-agent trace propagation. Compatible out of the box with LangGraph, Vertex AI, Azure AI Foundry, Bedrock AgentCore, and Pydantic AI.
Native semantic caching with per-request controls and cache key headers. Virtual key budgeting with hard spend caps enforced before cost is incurred. Intelligent load balancing with named fallback chains and automatic failover.
And all of it deploys on-premise. Docker or Kubernetes. Multi-architecture. Zero data egress.
The challenges we have documented over the past four months — shadow AI, MCP governance gaps, A2A blind spots, regulatory compliance — are not going away. They are intensifying. SmartFlow 1.3 is the infrastructure designed to address them.
Visit langsmart.ai to learn more or request a deployment assessment.
