Verified participation certificate
NitrostackMCP to the MoonWekan Enterprises

Certificate of Participation

This certificate is proudly presented to

Akshitha R

for participating as a member of team β€œDeepCraft” in the

Amrita University Amritapuri campus Hackathon

Jul 17-18, 2026

Abhishek Pandit signature

Abhishek Pandit

CEO, Nitrostack

Pablo JimΓ©nez Godoy signature

Pablo JimΓ©nez Godoy

CEO, Wekan Enterprises

Authenticity verified by NitroStack β€” https://nitrostack.ai/university/6a47e78ac305f1c3b0338b94/certificate/6a599bd3654f530279402cb6

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I participated in the Amrita University Amritapuri campus NitroStack Hackathon with DeepCraft.

Certificate: https://nitrostack.ai/university/6a47e78ac305f1c3b0338b94/certificate/6a599bd3654f530279402cb6

Team

DeepCraft

University

Amrita University Amritapuri campus

Hackathon dates

Jul 17-18, 2026

Track

Open Innovation

What they built

VIYAN: AI-Powered Autonomous Orbital Coordination Platform πŸš€

Space is entering its busiest era. With thousands of satellites already in orbit and tens of thousands more on the way, collision avoidance can no longer depend on fragmented communication and manual human decisions. A single mistake can create thousands of pieces of debris, triggering cascading collisions that threaten critical infrastructure, global communications, navigation, weather forecasting, and future space missions. VIYAN reimagines how satellites coordinate in space. Instead of simply detecting potential collisions, VIYAN enables autonomous, intelligent decision-making. Using real-time orbital data, our platform predicts future conjunctions, evaluates risk through a hybrid AI engine combining orbital physics with machine learning, and enables AI agents representing different satellite operators to negotiate the safest course of action. Unlike traditional systems that only generate warnings, VIYAN answers the critical question: "What should happen next?" Our platform performs the complete decision pipeline: Predicts future satellite trajectories. Detects potential conjunctions before they become dangerous. Evaluates collision probability using a hybrid physics + AI model. Negotiates between satellites based on mission priority and operational constraints. Recommends the safest maneuver with confidence scores. Explains every decision using Explainable AI (SHAP), ensuring transparency and trust. The result is a platform that transforms collision management from a reactive alerting system into an autonomous coordination ecosystem. Key Innovations πŸ›°οΈ Real-time orbital trajectory prediction. πŸ€– Hybrid AI risk assessment combining deterministic physics and machine learning. 🀝 Autonomous multi-agent negotiation between satellite operators. 🧠 Explainable AI with transparent reasoning behind every recommendation. πŸ“Š End-to-end decision support with timelines, confidence scores, and maneuver suggestions.

View codeSubmitted July 18, 2026
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