🤝 Top Collaborators
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🤓 Latest Submissions
RAKSHAK - Autonomy Evaluation Framework
RAKSHAK is an evaluation and benchmarking framework that validates autonomous robots before real-world deployment. As autonomous systems enter disaster zones, hospitals, warehouses, food and medicine delivery networks, agricultural pesticide spraying, and public infrastructure, failures are no longer minor bugs — they can result in injuries, recalls, lawsuits, and lost trust. Most autonomy failures occur in edge-case conditions not covered by standard testing. Field validation can cost $50K–$500K per failure iteration. RAKSHAK exposes these failures safely in simulation before deployment risk exists. Built on top of Webots for real-time 3D simulation, RAKSHAK transforms simulation into adversarial validation infrastructure. Instead of testing robots under ideal conditions, it injects 50+ structured chaos scenarios including battery degradation, sensor blackouts, communication loss, environmental hazards, network latency, and multi-agent conflicts derived from real-world robotics failure modes. The platform integrates LLM-driven autonomy using the Gemini API and runs cloud-deployed simulations on Vultr infrastructure with WebSocket-based real-time telemetry. It performs live stress injection and generates a quantified Trust Score (0–100) across safety, resilience, efficiency, communication reliability, and task completion. Example: A delivery drone carrying food or emergency medicine passes obstacle avoidance tests but crashes when battery drops below 20% during evasive maneuvers. RAKSHAK’s structured power-drop scenario exposes this weakness before first flight — preventing potential six-figure losses in hardware, liability, operational downtime, and public trust. This is not just simulation. This is measurable deployment readiness. As autonomous systems scale globally, validation must scale with them. RAKSHAK ensures robots are trusted before they are deployed.
15 Feb 2026
InsuranceAI -Instant Autonomous Insurance Settle
InsuranceAI rebuilds the insurance stack from first principles by eliminating human adjusters, opaque decision-making, and delayed payouts. Claims are evaluated and settled autonomously by AI agents and immutable smart contracts, delivering outcomes in seconds instead of weeks. At its core, InsuranceAI operates a multi-agent system powered by Google Gemini. When a user submits a claim—such as vehicle damage or health-related coverage—the agents analyze uploaded photos and videos in real time, verify policy conditions, and reach an immediate settlement decision. Every decision is cryptographically auditable and enforced on-chain, removing subjective judgment and operational friction. For parametric insurance, InsuranceAI removes the claims process entirely. Oracle data feeds continuously monitor predefined conditions such as flight delays or weather events. Once conditions are met, payouts are triggered automatically and settled instantly in USDC, without any user interaction. InsuranceAI introduces three core innovations aligned with the project’s Kill Shot objectives: • Parametric Mode: Fully automated, oracle-driven payouts with zero human involvement. • Privacy Toggle: Configurable privacy settings allow users to mask their identity while still proving eligibility and settlement validity using Arc’s privacy layers. • Reinsurance Pool: A decentralized staking pool enables the community to underwrite risk, earn yield from premiums, and collectively back insurance coverage. All claim data and settlement proofs are permanently anchored to Arweave for auditability, while a cross-chain evidence bridge ensures the integrity of off-chain inputs. By combining autonomous AI decision-making with instant blockchain settlement, InsuranceAI introduces a new insurance model that is fast, fair, private, and fully autonomous.
24 Jan 2026
Qubic Autopilot
Qubic Autopilot is an AI-powered DeFi operating system that turns natural language instructions into safe, fast and automated execution on the Qubic network. Users can express goals like “Swap 10% of my QUBIC into ETH every week” or ask questions like “Explain the current market trend,” and the multi-agent intelligence layer handles the entire lifecycle analysis, planning, risk validation, approval, and final execution through a real Qubic wallet. The system is powered by two cooperative AI roles: • Advisor : understands users, answers questions, explains markets, gives personalized insights, and helps refine strategies. • Agent : converts goals into executable plans, validates risks, and performs the actual operations through Qubic-connected tools. At its core is a virtual wallet system with real-time deposit detection, a transaction ledger, and a Smart Vault policy engine that enforces safety rules like daily spending limits, whitelists, max trade size, and emergency kill switches before any on-chain action is executed. The Smart Vault currently runs off-chain in Python, with a C++ Qubic smart contract version designed and simulated for future IPO deployment. The platform includes 50+ modular tools enabling swaps, staking, payments, oracle access, risk scoring, market analysis, and contract interactions. A human-in-the-loop approval pipeline ensures the user remains fully in control of important actions, while the system can automatically respond to real-time market conditions when strategies require it. Qubic Autopilot is the first end-to-end autonomous execution engine in the Qubic ecosystem, combining multi-agent AI, real mainnet integration, intelligent decision-making, and strong safety controls into a single production-ready automation layer for DeFi.
7 Dec 2025
