Enterprise AI & Workplace Automation PolarisSubmitted August 1, 2026

Decision Trace AI

An MCP app on the Model Context Protocol built by Polaris at the SRMIST NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

In any large organization, decisions are made every day — vendor rejections, infrastructure migrations, feature cancellations, project delays. But WHY those decisions were made? That institutional knowledge lives scattered across emails, meeting notes, finance reviews, and spreadsheets. "When someone asks why did we reject Vendor X? — nobody can answer it without a 30-minute archaeology expedition through old Slack threads and shared drives." DecisionTrace AI solves this. It gives anyone in the organization a single natural-language search bar to instantly trace and replay any business decision — powered by MCP

Enterprise AI & Workplace Automation track

Develop AI agents and automation tools that improve productivity, streamline workflows, and enhance business operations.

Team Polaris

  • Krishita Satish KumarLead

  • ARCHISHA R

  • Gopesh Vijay

  • Bharath Sayani

Frequently asked questions

What does Decision Trace AI do?
In any large organization, decisions are made every day — vendor rejections, infrastructure migrations, feature cancellations, project delays. But WHY those decisions were made? That institutional knowledge lives scattered across emails, meeting notes, finance reviews, and spreadsheets. "When someone asks why did we reject Vendor X? — nobody can answer it without a 30-minute archaeology expedition through old Slack threads and shared drives." DecisionTrace AI solves this. It gives anyone in the organization a single natural-language search bar to instantly trace and replay any business decision — powered by MCP
Who built Decision Trace AI?
Decision Trace AI was built by team Polaris at the SRMIST NitroStack × MCP To The Moon hackathon, in the Enterprise AI & Workplace Automation 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.