Section 9 – How Raindrop Enables Agentic Procurement

Agentic Procurement in Raindrop

Raindrop enables agentic procurement through a platform that has been specifically designed for the operating model. It provides a unified Source-to-Pay suite built with AI as a foundational component — it is part of every process from the start. Raindrop eliminates the need to deal with fragmented systems by integrating procurement workflows into a single platform with a normalized data model, allowing agentic agents to operate across the full procurement lifecycle. 

Raindrop enables agentic procurement through Rain — our unified AI layer that brings together conversational intelligence, workflow execution, and proactive orchestration across the procurement lifecycle

• Rain AI Agent: A conversational interface for procurement tasks that lets users interact with it using natural, conversational language. Ask questions, request actions, initiate workflows, and much more. There are three types of agents under Rain:
  • Query Agents: Help users understand and answer procurement questions across spend, contracts, sourcing, suppliers, and performance data — turning complex information into clear next steps.
  • Action Agents: Expand from answering questions to executing work. These agents help turn insights into action by creating sourcing events, recommending award scenarios, identifying contract overlap, and initiating workflows.
  • Proactive Agents: Agents that monitor, anticipate, and act. These agents identify risks and opportunities in real time, such as tail spend opportunities, market pricing shifts, or high-risk renewals, and initiate the appropriate workflow for review.
• MCP Integration: Through the Model Context Protocol (MCP), external LLMs may access Raindrop data. This enables real-time interactions between the AI agents and enterprise platforms. 
• System Awareness: Agents retrieve real-time information from procurement workflows, allowing them to gather up-to-date information from sourcing events, invoices, suppliers, contracts, and other given resources. With this access, all decisions can be based on accurate contextual information.
• Action Layer: Agents aren’t limited just to providing generated insights. Instead, they can take action. This can include triggering workflows and system actions, like initiating approvals and executing procurement processes directly within the system. 

Example Flow

Take a look at this example flow to see how Raindrop enables agentic procurement. 

• The user asks: “How many contracts do I have for SAP Americas?”
• The agent queries Raindrop contract data
• The agent analyzes results
• The agent generates a summary and a recommendation
• The agent initiates the NDA or the new contract workflow

This flow shows how agentic AI operates with Raindrop. It:

• Connects data across systems
• Analyzes context in real time
• Generates actionable insights
• Executes workflows

The final result? A system that seamlessly transitions your question from a prompt to an outcome. Procurement work is no longer handled manually, but instead driven by AI.