Research & Operational Findings

Pluggedspace Console: An Enterprise Agentic Operating System with Unified Memory Substrate, Tool SDK, and Marketplace for Cross-Agent Intelligence Transfer

The rapid proliferation of Large Language Models (LLMs) has shifted the paradigm from simple conversational AI to autonomous agents capable of executing complex business workflows. However, existing agent frameworks often suffer from "memory silos," where specialized agents cannot share learned context, creating inefficiencies and limiting cross-domain insight generation. We present **Pluggedspace Console (v4)**, an enterprise Agentic Operating System whose primary contributions include **BrainBox** (a unified memory substrate), a **Tool SDK** with 28 tools, a **Tenant Agent Builder** for custom agent creation, a **Marketplace** for agent sharing, and an **Observability Dashboard**. BrainBox utilizes a four-layer architecture comprising an Event Store, Semantic Memory (via pgvector), a Knowledge Graph, and an Inference Layer, enabling heterogeneous agents to collaborate through shared semantic, episodic, relational, and inferential memory while maintaining strict tenant isolation. The system has evolved through four major iterations: V1 (siloed agents), V2 (shared Runtime Engine and dynamic Tool Registry), V3 (unified SDK, Artifact Store, Memory Bus API, Policy API, Observability, Tenant Agents, Marketplace), and V4 (enhanced ecosystem with 28 tools, Skills System, Background Scheduler, Package System, and Console Interface). To ensure operational safety in high-stakes enterprise environments, Pluggedspace Console implements Human-in-the-Loop (HITL) orchestration through a centralized Approval Queue with configurable autonomy modes and a formal Policy Engine for constraint-based governance. We evaluated the system using enterprise workloads across seven agent verticals and 28 tools, observing improvements in memory efficiency (37% LLM call reduction), cross-agent intelligence transfer (84% entity propagation), HITL safety (100% high-risk interception), and modular deployment (90% time reduction). Our results suggest that unified memory architectures combined with SDK tooling and marketplace ecosystems have the potential to transform memory from a per-agent cost center into a shared system resource.