Sonica Gill@SonicaGill

Voice Notes Assistant turns spoken audio — meetings, lectures, interviews, or personal voice memos — into clean, readable text in seconds. Record directly in the browser or upload an audio file, and Speechmatics' speech recognition engine handles the heavy lifting of turning speech into an accurate transcript, in either English or Urdu. What sets it apart is how it handles real conversations with multiple speakers. Rather than relying solely on automatic speaker detection, users can record or upload separate clips for each speaker, label them (e.g. "Speaker 1," "Interviewer," a name), and add them one by one to a running queue — nothing is lost between additions. When ready, the app transcribes every clip and stitches them into a single, clearly labeled transcript. Speechmatics' built-in diarization is also available for cases where multiple people are already talking in one recording. Once transcribed, a lightweight, fully local TextRank summarization algorithm — no paid summarization API required — extracts the most important sentences into a concise summary, with an adjustable length from 1–6 sentences. Both the transcript and summary are shown in an in-app preview first, so users can review the content before choosing to download it as a .txt file, rather than a file landing on their machine unreviewed. The interface is designed to feel like a genuinely bilingual tool rather than an English app with Urdu bolted on: Urdu output renders in real Nastaliq script with correct right-to-left layout, not transliterated Latin text. The API key is never exposed in the browser — it's read securely from a server-side environment variable — and the whole experience is wrapped in a playful, mobile-app-inspired dark UI with a mint accent, flag-based language indicators, and rounded, tactile control

he Resource Allocation Optimizer is an innovative AI-driven solution designed to address the challenges of bandwidth allocation in public sector networks, particularly in underserved regions. Public sector connectivity networks often face issues like resource scarcity, suboptimal prioritization, and inefficiencies in service delivery for critical sectors such as healthcare, education, and emergency services. This system leverages the power of Groq's Llama API to analyze incoming service requests and assign numerical priority scores based on urgency, bandwidth requirements, and the nature of the service. These prioritized requests are then processed by a dynamic resource allocation algorithm that distributes available bandwidth in real-time, ensuring that high-priority services receive the resources they need without delays.Key features of the project include: Simulated Environment: A network simulation generates realistic service requests for bandwidth from sectors like healthcare, education, and emergency services. AI-Powered Decision Making: The Groq Llama model analyzes requests and assigns priorities, enabling fast and accurate resource allocation. Dynamic Resource Allocation: The allocation algorithm ensures bandwidth is distributed efficiently, balancing critical needs and overall network availability. Interactive Dashboard: Built using Streamlit, the dashboard visualizes service logs, priorities, and bandwidth usage with real-time updates and dynamic charts, offering transparency and user engagement. This project has immense value in enhancing the efficiency of public sector networks by automating resource management, improving service outcomes, and reducing operational overhead. It is designed with scalability in mind, allowing integration with real-world networks and enabling further customization for specific scenarios.

🌎 Hybrid Hackathon | 💻 Online Build: September 10–16, 2026 | 📍 On-site: September 15–17, 2026 The official hackathon of AI Infra Summit — co-organized by Kisaco Research and lablab.ai. Build production-grade AI applications on the modern AI infrastructure stack, alongside 8,000+ attendees, researchers, founders, and infra leaders. 📍 On-site Venue (September 15–17): Santa Clara Convention Center 5001 Great America Pkwy, Santa Clara, CA 📍 On-site participation is by invitation only. Travel and accommodation expenses will not be covered.

⏱️ Design, build, and deploy trustless AI trading agents. 📅 March 30 – April 12, 2026 🌐 Build AI trading agents that execute strategies using ERC-8004 or Kraken CLI. 🤝 Build solo or in teams to create autonomous trading, risk, yield, or protection agents. 💰 $55,000 prize pool, allocated and shared via Surge and Kraken. Your team should have registered project at early.surge.xyz in order to be eligible for the prize. Get access in your team profile or our discord 🔑 Access to early.surge.xyz If prompted for login credentials, use: • Username: admin • Password: JBRv2xWG7AzwVrLz88

Teams work together with multiple AI agents in shared workspaces to design, build, and launch complete AI products — from initial idea to market-ready app. 📅 February 23– March 1, 2026 ⏱️ 6 days to build and ship an end-to-end agentic AI product 🤝 Work together in shared AI workspaces where your team and AI agents collaborate in real time 🔧 Build with multiple AI agents that handle development, design, testing, and documentation together 🎯 Create everything in one place — from ideation to product to marketing materials, all by prompting and observing 🚀 Focus on real-world products that teams could actually ship and use 🏆 $3,500 in prizes + premium 3-month Complete.dev access for top teams 🧑‍💻 Join your team workspace and start building together