BFSI & FinTech Team bruteforceSubmitted July 18, 2026

VendorIQ - Agentic AI Procurement Decision engine

An MCP app on the Model Context Protocol built by Team bruteforce at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

VendorIQ is an Agentic AI Procurement Decision Engine designed to help procurement teams make faster, smarter, and more transparent vendor selection decisions. Today, enterprise procurement is a manual and fragmented process. When a department requests an item (e.g., laptops, servers, networking equipment), procurement teams must gather information from multiple systems such as vendor databases, historical contracts, supplier performance records, compliance documents, and market pricing before selecting a vendor. This process is time-consuming, repetitive, and heavily dependent on the experience of procurement professionals. VendorIQ transforms this workflow using a team of specialized AI agents. A user simply describes their procurement requirement in natural language, and the agents autonomously understand the request, identify suitable vendors, evaluate vendor performance, analyze historical contracts, generate negotiation strategies, rank vendors using explainable decision scoring, and recommend the most suitable procurement strategy. Unlike traditional procurement software that only stores information or displays dashboards, VendorIQ actively reasons across enterprise data to support decision-making. Every recommendation is accompanied by an Explainability Tree, allowing users to understand exactly why a vendor was selected based on factors such as cost, delivery performance, quality, compliance, historical relationships, and risk. Additionally, the What-If Simulation Agent enables procurement managers to compare alternative vendors and instantly visualize the impact on cost, delivery timelines, warranty, and overall risk before making a final decision. The platform is intended for procurement teams, supply chain managers, and enterprise purchasing departments seeking to reduce procurement time, improve vendor selection quality, and make AI-assisted procurement decisions with confidence. What makes VendorIQ unique is that it does not function as a chatbot

BFSI & FinTech track

Build AI solutions for banking, payments, insurance, fraud detection, lending, and financial inclusion.

Live MCP appSource code

Team Team bruteforce

  • Velamala Pavan KrishnaLead

  • Ulligadda Shashank

  • Nallapaneni Vaibhav

  • Adithya Varma Kusampudi

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Frequently asked questions

What does VendorIQ - Agentic AI Procurement Decision engine do?
VendorIQ is an Agentic AI Procurement Decision Engine designed to help procurement teams make faster, smarter, and more transparent vendor selection decisions. Today, enterprise procurement is a manual and fragmented process. When a department requests an item (e.g., laptops, servers, networking equipment), procurement teams must gather information from multiple systems such as vendor databases, historical contracts, supplier performance records, compliance documents, and market pricing before selecting a vendor. This process is time-consuming, repetitive, and heavily dependent on the experience of procurement professionals. VendorIQ transforms this workflow using a team of specialized AI agents. A user simply describes their procurement requirement in natural language, and the agents autonomously understand the request, identify suitable vendors, evaluate vendor performance, analyze historical contracts, generate negotiation strategies, rank vendors using explainable decision scoring, and recommend the most suitable procurement strategy. Unlike traditional procurement software that only stores information or displays dashboards, VendorIQ actively reasons across enterprise data to support decision-making. Every recommendation is accompanied by an Explainability Tree, allowing users to understand exactly why a vendor was selected based on factors such as cost, delivery performance, quality, compliance, historical relationships, and risk. Additionally, the What-If Simulation Agent enables procurement managers to compare alternative vendors and instantly visualize the impact on cost, delivery timelines, warranty, and overall risk before making a final decision. The platform is intended for procurement teams, supply chain managers, and enterprise purchasing departments seeking to reduce procurement time, improve vendor selection quality, and make AI-assisted procurement decisions with confidence. What makes VendorIQ unique is that it does not function as a chatbot
Who built VendorIQ - Agentic AI Procurement Decision engine?
VendorIQ - Agentic AI Procurement Decision engine was built by team Team bruteforce at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon, in the BFSI & FinTech track.
What is an MCP app and how is it built?
An MCP app is an application built on the Model Context Protocol — an open standard that lets AI agents connect to tools, data, and APIs. This project exposes MCP tools and resources that agentic AI systems can call. It was built and deployed on NitroStack, the full-stack platform for shipping MCP apps and servers.