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🤝 Top Collaborators
🤓 Latest Submissions
Recap - Turn a conversation into notes
Recap is a voice-driven notetaking assistant built for the AI Infra Summit Hackathon that turns any spoken conversation — a standup, an incident call, a planning session — into notes you can actually act on. Instead of asking someone to type furiously while everyone else talks, Recap listens. It streams live, real-time transcription of the conversation straight to the screen using Speechmatics' real-time speech-to-text API, showing partial words settle into a final transcript as people speak, so nothing has to be reconstructed from memory afterward. The moment the conversation ends — or at any point during it — a single click sends that transcript to Groq, which reasons over the raw text and returns a fully structured recap: a concise summary, the key points that were actually discussed, action items paired with their owners, decisions that were made, and any open questions that were left unresolved. Rather than leaving a team to skim a wall of transcript, Recap organizes it automatically into the exact shape a team actually needs after a call. Beyond the static recap, Recap also lets anyone query the conversation directly through a built-in ask box: instead of scrolling back through the whole transcript to find out what was decided about a rollout or who owns a follow-up, you can just ask, and Groq answers using only what was actually said in that conversation — grounded, not guessed. The entire experience lives in a single, dependency-light web page: no backend server to deploy, no database to maintain, just a browser tab that can record live audio or accept a pasted transcript, generate notes, and answer questions in real time. Built by Mirza Yasir Abdullah Baig, Hamna Munir, Tayyeba Saleem, Zainab Khan, and Sheikh Abdul Rehman, Recap demonstrates what's possible when a fast real-time transcription layer (Speechmatics) is paired with a fast structured-reasoning layer (Groq)
16 Sep 2026
QuantumDEX
QuantumDEX is an AI-powered decentralized exchange built natively on the Qubic Network to stop value leakage in DeFi trading. Today, users routinely overpay because swap routers check only a limited set of paths and ignore fragmented liquidity across chains, pools, and fee tiers. Our idea is to treat every trade as an optimization problem instead of a single DEX call. QuantumDEX runs machine-learning models on top of Qubic’s computational layer to simulate and evaluate thousands of potential routes in parallel before a transaction is sent on-chain. For each swap, we predict slippage, gas impact and MEV risk, then construct the route that maximizes the user’s expected output while honoring their constraints on speed and risk. Under the hood, QuantumDEX consumes on-chain and mempool data, updates models continuously, and exposes the intelligence through a simple, non-custodial interface and a developer-friendly routing API. Traders just connect a wallet and swap; integrators can plug our smart router into wallets, aggregators, or DeFi protocols. By combining scalable compute with adaptive ML, QuantumDEX aims to become the execution layer for Qubic-based DeFi, increasing capital efficiency for liquidity providers and giving end-users consistently better prices across all available pools.
7 Dec 2025
