Platform Architecture

The logical view of the platform, top to bottom — from the agents people interact with down to the systems your data already lives in. Every layer is independently swappable; click any layer to see what it is, why it matters, and how it works.

ibl.ai Platform

Agents

Autonomous task execution across the platform

ibl.ai Switchboard Layer

Routing

Request orchestration & MCP

Security & Guardrails

Role-based access control

LLMs (Model Agnostic)

GPT, Claude, Gemini, open-source — swappable

Ontological Layer

Structured knowledge, semantic relationships

Data Lake

Unified institutional data store

Apps & Data Silos

SIS, LMS, CRM, third-party systems

How the ibl.ai platform is built

ibl.ai is an Agentic AI Operating System organizations deploy on their own infrastructure. The stack spans a data and integration layer, a per-entity memory layer, an agent orchestration layer, and model-agnostic LLM routing — so you can swap providers without rebuilding.

Agents connect to your existing systems — LMS, SIS, CRM, and ERP — through MCP-based interoperability. Each agent has defined roles, access controls, and review cycles, and every interaction runs through the platform’s safety and moderation layer.

Deploy in the cloud, on-premise, or fully air-gapped. You keep full source code, full data control, and the freedom to run any LLM — OpenAI, Anthropic, Google, Meta, or self-hosted open-weight models.

Explore the platform