LiveAIAI Agent

Clara

AI Source-to-Pay Agent

An AI agent that automates enterprise procurement across Procol, Ariba, Coupa, and SAP — with episodic memory and multi-platform event-driven publishing.

The problem

Enterprise procurement data and actions live across disconnected systems — Procol, Ariba, Coupa, SAP — each with its own event model and integration contract. Building point-to-point integrations for every new client was slow, brittle, and high-maintenance.

The approach

  • Introduced a mediator pattern to decouple producers from platform-specific adapters.
  • Used MCP (Model Context Protocol) as a standard integration surface so tools and platforms can plug in consistently.
  • Built a dedicated AI orchestration service to decide what to publish, where, and when.
  • Added a Long-Term Memory Store for episodic context across sessions so Clara remembers what happened last time.

Architecture

Clara architecture diagram showing main components and data flow.
Clara architecture overview.
  • Producer emits domain events into a central mediator.
  • Mediator routes events to platform adapters (Procol, Ariba, Coupa, SAP) and to the AI service.
  • AI service reads from and writes episodic memory to the Long-Term Memory Store.
  • MCP layer exposes tools and capabilities to the agent without leaking each platform's internals.

Impact

Reduced integration TAT for new enterprise clients

Enabled multi-platform publishing from a single source

Agent sessions now carry context across conversations

What I learned

  • A mediator earns its complexity when the adapter count is >2 and contracts keep changing.
  • Episodic memory changes user expectations — users start treating the agent like a colleague, not a search box.

Tech

Ruby on RailsEvent-Driven ArchitectureMCPAI ServicesPostgreSQLRedis
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