BFSI & FinTech Team mulazzSubmitted July 26, 2026

INSTANTPULSE

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

About this project

When a new business wants to accept card payments or borrow money, it fills in forms, uploads bank statements, and then waits **three to five business days** while someone at the bank reads those statements by hand. That wait is expensive for everyone. The business cannot trade. The bank pays skilled analysts to do repetitive work. And because the review is manual, two analysts looking at the same statements can reach different conclusions — with no written record of why. The evidence needed to make the decision is already sitting in the business's bank account. The delay is not analysis; it is queueing. ## 2. What InstantPulse does The business securely connects its bank account. InstantPulse then: 1. Pulls the transaction history 2. Analyses cash flow, income stability, expenses, debt patterns and unusual transactions 3. Produces a **transparent risk score** out of 100, with a written reason for every point awarded or withheld 4. Recommends a **credit limit**, and says which constraint capped it 5. Classifies the application: - 🟢 **Green** — ready to proceed - 🟡 **Yellow** — human review required - 🔴 **Red** — high risk or missing information 6. For Green applications, automatically starts **Stripe** payment-account onboarding 7. Gives managers a live dashboard explaining the decision, the risk factors and the next action Three to five days becomes **one call**. In offline mode a full decision takes about 30 milliseconds; against the live Plaid API it takes about 15 seconds. Crucially, it does **not** replace credit officers. Yellow applications go into a real review queue where an officer can request documents or override the decision — with a written justification that is recorded permanently.

BFSI & FinTech track

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

Team Team mulazz

  • chilukuri subrahmanya sri prakashLead

  • Yartha Vinutha

  • KJSK-Koushik

  • Akhil

Frequently asked questions

What does INSTANTPULSE do?
When a new business wants to accept card payments or borrow money, it fills in forms, uploads bank statements, and then waits **three to five business days** while someone at the bank reads those statements by hand. That wait is expensive for everyone. The business cannot trade. The bank pays skilled analysts to do repetitive work. And because the review is manual, two analysts looking at the same statements can reach different conclusions — with no written record of why. The evidence needed to make the decision is already sitting in the business's bank account. The delay is not analysis; it is queueing. ## 2. What InstantPulse does The business securely connects its bank account. InstantPulse then: 1. Pulls the transaction history 2. Analyses cash flow, income stability, expenses, debt patterns and unusual transactions 3. Produces a **transparent risk score** out of 100, with a written reason for every point awarded or withheld 4. Recommends a **credit limit**, and says which constraint capped it 5. Classifies the application: - 🟢 **Green** — ready to proceed - 🟡 **Yellow** — human review required - 🔴 **Red** — high risk or missing information 6. For Green applications, automatically starts **Stripe** payment-account onboarding 7. Gives managers a live dashboard explaining the decision, the risk factors and the next action Three to five days becomes **one call**. In offline mode a full decision takes about 30 milliseconds; against the live Plaid API it takes about 15 seconds. Crucially, it does **not** replace credit officers. Yellow applications go into a real review queue where an officer can request documents or override the decision — with a written justification that is recorded permanently.
Who built INSTANTPULSE?
INSTANTPULSE was built by team Team mulazz at the Amrita University Coimbatore 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.