Rain doesn’t just answer questions — it takes on goals. In this demo, Rain analyzes the supplier base, flags spend leakage and control gaps, and builds a prioritized 90-day action plan — surfacing invoices without POs, contracts, and one critical finding: significant IBM spend with no contract on file.
Rain doesn’t stop at analysis. It proposes the next action, creates the contract record, and drafts the agreement — with humans in the loop at every step.
Watch how Rain moves procurement from insight to action, faster.
Video Transcript
Agentic AI in procurement is about more than asking a question and receiving an answer. It is about giving an intelligent agent a goal, allowing it to analyze the underlying data, recommend a course of action, and help execute the work.
In this example, I’ve asked Rain to analyze our supplier base, assess spend leakage, identify control gaps, and build a prioritized 90-day action plan.
Rain immediately begins examining our top supplier spend and looking for red flags—such as invoices that don’t match purchase orders, spend that isn’t supported by a contract, or categories that are overly concentrated among only a few vendors.
Because the process is transparent, I can follow Rain’s reasoning as it works through the analysis.
Rain returns a summary, a clear dashboard, and a prioritized 90-day plan, with spend leakage at the top of the list.
Rain also highlights two major gaps: invoices without POs and spend without contracts.
Rain flags suppliers pending registration, contracts approaching expiration, and one critical finding: significant IBM spend with no contract on file.
The most urgent action is clear: create a contract for IBM.
Rain does not simply tell me what should happen next. It asks whether it can help take the next action and proposes creating the IBM contract. I approve, and Rain gets to work.
This is where Agentic AI goes beyond analysis.
Using the information already available, Rain creates the contract record and populates the relevant details. When information is missing, Rain leaves the field open for a human to review and complete—keeping the human firmly in the loop.
Next, I’m ready to draft the agreement. But why start from scratch when generative AI can create it using our preferred terms, conditions, and approved clauses?
I select the clauses I want to include, and Rain generates the agreement and attaches it to the contract, ready for legal review and signature.
Finally, I ask Rain how much time I just saved.
Rain provides a breakdown of the work it completed, how long each step took, and how much manual effort those same activities would typically require.
It shows how quickly Rain moved from analyzing supplier data to identifying risk, building a plan, creating a contract record, and drafting the agreement.
Rain also reminds me that this estimate only reflects the visible work—not all the coordination, follow-up, and back-office activity that normally happens behind the scenes.
That means I’m not only saving time. I’m also reducing delays and keeping the entire process moving forward.
I say thanks, and Rain lets me know it’s ready to help with the next step.
With Rain, procurement moves from insight to action—faster, smarter, and in control.
