Krrish solves the core strategic problems. At Tusk Investments he designed a systematic trading strategy that reached a Sharpe of 4.02. At MicroSave Consulting he built regime-detection models for a $1M multi-asset mandate to navigate shifting market conditions. At Sparrow Capital he sized a market from the bottom up to uncover a 10x mispricing. He also co-wrote the memo behind a ₹3.3 crore seed round. As Director of Research and Strategy at IFSA, IIT Kharagpur, he leads a team of 30. He turns complex business challenges into actionable, data-backed decisions.

Devansh does the research that goes in front of investors. At Dinero Capserv he covers everything from space hardware to AI. This includes modelling a $12M ARR company's path to $100M ahead of a Series B. At MicroSave Consulting Singapore he built a 4-state regime model over 10 years of data for a $1M mandate. At Sparrow Capital he caught a 10x mispricing by reconciling top-down sizing against bottom-up unit economics. He is Director of Finance at IFSA and a CFA Level 1 candidate. He writes equity research notes that hold up when someone disagrees with them.

Nidhi builds the systems. She is an AI Engineering Intern at Design Industries in Australia. There she built retrieval workflows using a company's Jira and Confluence as live memory. She also built a pipeline that reads written specifications and produces working automations. Before that she spent 6 months on computer vision research at IIT Kharagpur. She analysed 500+ hours of traffic footage to estimate pedestrian safety risk. Her document intelligence pipeline processes 500+ unstructured PDFs with 35% fewer extraction errors. She is a Codeforces Specialist with 200+ problems solved.

Mayank builds models and checks whether they can be trusted. At Design Industries in Australia he built safety guardrails that cut invalid AI responses by 30%. His civic AI portal runs a 4-layer safety pipeline catching 87% of unsafe prompts across 100+ test cases. He makes machine learning useful rather than impressive. He built a churn model at 85.3% F1 with per-customer explanations attached. He also built a recommendation system that lifted catalogue coverage from 3.69% to 13.14% by fixing popularity bias. He co-authored the pedestrian safety research at IIT Kharagpur.

Umang works on whether things actually worked. He ran an A/B test on a checkout change worth roughly $1.83M a year on desktop. It was worth nothing at all on mobile. Most teams miss this distinction by reading 1 blended number. He built a hotel management system covering 40 rooms and 8 staff, cutting invoice time from 15 minutes to 2. He founded KGP Rides, a cab-sharing platform for students flying through Kolkata. He was 1st runner-up at Open IIT Product Management for an AI procurement system.

Yash writes the specification and makes sure it ships. At Mahila Money he designs verification workflows across 20+ scenarios for an AI-first lending platform. He maps how 4 separate agents hand work between each other. At Bloom Hotels he built booking and invoicing automation that moved 30% of bookings direct and cut invoice time by 87%. He founded KGPFind, a lost-and-found platform serving 15,000+ campus residents that replaced 50 WhatsApp groups. He was a national finalist at the Indian Case Challenge for Hindustan Unilever. He runs public relations and web for IIT Kharagpur's Entrepreneurship Cell.

Kaustubh builds the things underneath. At Novalab Healthcare he built a Next.js and FastAPI platform that cut patient query response time by 40% and manual order processing by 35%. His work runs deeper than most application code. He built a C++ file compression engine using Huffman encoding. He built a Rubik's cube solver implementing Korf's IDA* algorithm. He also built a nearest-neighbour search system on KD-trees and random projection trees. He was elected Entertainment Secretary of the Technology Students' Gymkhana with 1,800+ votes, managing a ₹3 lakh budget across 9 major events.