Vendor-Neutral Multi-Cloud Control Plane

Safely Write AI & ML Decisions Back into Operational Databases.

The multi-cloud BYOC control plane for predictive models, batch enrichment, and AI agents. Eliminate production table locks across serverless (Neon, Supabase, Turso) and enterprise engines (PostgreSQL, SQL Server, Fabric, Snowflake, Iceberg) inside your cloud perimeter.

0 Production Table Locks Multi-Cloud (AWS / Azure / GCP) & Serverless <15ms In-Memory Masking
Interactive Execution Pipeline

Real-Time Operational Write-Back Simulation

In-VPC Egress-Only PrivateLink
1. AI Inference / Agent Tool Call
REQUEST_INITIATED

Probabilistic prediction score or tool invocation dispatched via Model Context Protocol (MCP) or HTTP/2 REST API.

protocolJSON-RPC 2.0 (MCP) / gRPC
payload{ entity_id: 'CUST-90142', score: 0.94, model: 'xgb-v2.4.1' }
tokenizationIn-memory dynamic schema pruning (-74% prompt tokens)
Integration & Model Topology

Where Do Models Live & How Does Data Flow?

3 Real-World Integration Patterns

Pattern A: AI Agents & LLM Tool Calling

Claude, GPT-4o, Cursor, LangGraph, AWS Bedrock
Native MCP (JSON-RPC 2.0 via SSE / stdio)

Agents query and propose database mutations through Anthropic's Model Context Protocol. Progressive disclosure prevents prompt context saturation, and sensitive attributes are masked locally inside your customer VPC.

Where Model LivesAnthropic / OpenAI / Bedrock API
How It Talks to MeynosMCP JSON-RPC 2.0 (Port 443 / SSE)
In-VPC ValidationCedar PDP + Ephemeral CoW Sandbox
Target DatabasePostgreSQL / Neon Serving Tables
integration_recipe.ts
// 1. Agent Connects to In-VPC MCP Gateway
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse.js";

const transport = new SSEClientTransport(
  new URL("https://mcp-gateway.customer.internal/sse")
);
const client = new Client({ name: "ClaudeAgent", version: "1.0.0" });
await client.connect(transport);

// 2. Agent Discovers Pruned Tools Dynamically
const tools = await client.listTools(); 
// Returns: ['query_serving_risk', 'propose_transient_write']

// 3. Agent Calls Tool (Dry-Run on Ephemeral Neon Branch)
const response = await client.callTool({
  name: "propose_transient_write",
  arguments: {
    customer_id: "CUST-90142",
    score: 0.94,
    model_version: "claude-3-5-sonnet"
  }
});
Core Architecture

Five Pillars of Governed Operational AI Feedback

Built for enterprise data teams running PostgreSQL, SQL Server, Neon, Supabase, and Iceberg.

Interactive Control Plane Sandbox

Live In-VPC Policy & Sandboxing Inspector

Execution Context
Threshold: >= 0.88 required for auto-promotion
PERMITTED (Serving)1.2ms PDP
policy.cedar
// Open-Source Cedar ABAC Decision Point (In-VPC/In-VNet)
permit(
  principal in AgentRole::"OperationalScoringAgent",
  action in [Action::"AssertTransientWrite", Action::"PromoteToServing"],
  resource in Table::"serving_customer_risk_scores"
)
when {
  context.model.confidence >= 0.88 &&
  context.agent.delegation_depth <= 2 &&
  resource.is_serving_table == true
};
Frequently Answered Questions

Technical & Architecture Insights