Press Release

You can put an OpenAI-compatible gateway in front of an existing application by changing one line. No SDK swap, no client rewrite, no application redeploy beyond the config change. This guide shows how Vaikora's drop-in proxy applies the same security policy across 12 LLM providers with provider fallback routing.

An AI agent control plane is a single inline enforcement layer that applies the same deterministic policy engine, probabilistic risk scoring, and tamper-evident audit log across every AI agent protocol. This guide explains why each protocol's native controls are insufficient on their own, presents Vaikora's protocol-agnostic enforcement architecture.

This is a reference architecture for securing AI agents with an inline proxy layer. The design has five layers — Middleware, AuthN/Z, Interceptor Proxy, Threat Detection and Enforcement, and Audit and Compliance — arranged in fixed order between the agent and the upstream LLM or partner agent.

ACP (Agent Communication Protocol) and ANP (Agent Network Protocol) are the two AI agent protocols most teams encounter after MCP and A2A. This guide defines each acronym on first use, covers their architectures with example payloads, ends with a decision matrix mapping project types to protocol fit, and shows where Vaikora applies a single enforcement layer across both.

You stop PII from leaking between AI agents by placing a deterministic policy enforcement layer (with probabilistic risk scoring) inline on the A2A task hand-off, so every task message is inspected, classified, and either redacted or blocked before it reaches the Remote-Agent. Concretely, A2A traffic flows through Vaikora as a transparent egress

A2A defines a Task-Based Actor Model — a User sends work to a Client-Agent, which then delegates to one or more Remote-Agents — and a discovery mechanism based on agent cards published at /.well-known/agent.json. This guide shows how Vaikora applies inline policy enforcement on every A2A task message before it crosses an organizational boundary.

MCP is the answer to a simple question: how does an LLM call a tool, read a database, or open a file in a way that any compliant AI application can consume? This guide explains the architecture, the transport layer, and three concrete use cases — and shows where a runtime control layer like Vaikora fits.

This guide explains exactly why "log everything" conflicts with SOC 2, HIPAA, GDPR, PCI DSS, ISO 27001, NIST CSF, and CCPA, and presents the metadata-only logging pattern (content: false) plus a SHA-256 hash chain that satisfies the same evidence requirements without storing prompts.

AI gateway, DLP, and WAF solve different problems and do not substitute for each other. A WAF (Web Application Firewall) inspects HTTP traffic for known web-attack patterns. A DLP (Data Loss Prevention) tool detects sensitive data in files, email, and endpoint flows.