Dyunetra whitepaper.

Abstract

Dyunetra (Dyu-Netra — "the eye of the sky") is a technology company born from Team Dyunetra, the Bajaj Institute of Technology student team that won the national Smart India Hackathon 2022 (Software Edition) on problem statements from the India Meteorological Department and Ministry of Earth Sciences. The company builds cybersecurity, blockchain and AI products united by one idea: technology you can verify, explain and trust.

The problem

Organisations are asked to trust systems they cannot inspect. Security tools hide their reasoning behind black-box scores. AI systems act without accountability. Investigations depend on evidence whose handling cannot be proven. Trust is asserted, not demonstrated.

Our thesis

Every action attributable. Every finding explainable. Every system under your control. We design platforms where evidence is cryptographically protected, AI decisions carry human-readable rationale, and sensitive work runs offline-first, without depending on infrastructure you cannot audit.

Product portfolio

• MEVONU — Open DFIR Intelligence Platform. Offline-first, AI-assisted digital investigation where every action is cryptographically attributable and every finding carries a human-readable rationale.
• QEVRAXIS — Quantum intelligence and adaptive protection. Deep-learning network defence (CNN-Bi architectures, trained on CIC-IDS2017, CSE-CIC-IDS2018 and UNSW-NB15) with real-time monitoring and a centralised dashboard.
• DevAI — Secure AI Workforce Platform. Governed AI employees that automate research, reporting and coding support with approved access, human oversight and auditable execution.

Design principles

• Evidence first — claims are backed by data you can inspect.
• Explainable by default — no result ships without a rationale a person can read.
• Offline-first — capability must not depend on connectivity you do not control.
• Human-in-the-loop — automation assists; people decide.
• Independent verification — audit trails you can check yourself.

Roadmap direction

Deepening the AI assistance inside MEVONU's investigation workflow, expanding QEVRAXIS's model coverage and response automation, and growing the DevAI governed-workforce runtime for specialised enterprise roles. Consulting engagements feed learnings back into the platforms.