Tehreem Ayesha@tehreem_ayesha
1
Events attended
1
Submissions made
Pakistan
1 year of experience
About me
I'm Tehreem Ayesha, an Energy Systems Engineering graduate from Pakistan with a growing passion for AI and its applications in solving real-world challenges. Coming from a non-technical background, I began learning AI from scratch, which has strengthened my curiosity, adaptability, and commitment to continuous learning. My interests lie at the intersection of AI, sustainability, and engineering. I've built AI-powered applications, including Retrieval-Augmented Generation (RAG) chatbots, and enjoy exploring how intelligent systems can make technical solutions more accessible and impactful. I'm particularly interested in applying AI to energy, agriculture, and climate-related problems. I enjoy participating in hackathons because they push me to learn quickly, collaborate with diverse teams, and turn ideas into working prototypes under tight deadlines. I'm always eager to connect with builders, researchers, and innovators who are passionate about creating technology with meaningful real-world impact.
🤝 Top Collaborators
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🤓 Latest Submissions
fairshare
Splitting bills with roommates sounds simple, but rarely is. Most expense apps, Splitwise included, assume everyone contributes and consumes equally, defaulting to an equal split for rent, groceries, electricity, and gas. In real shared living, that assumption breaks down. One flatmate runs the AC for six hours a day, another barely touches it. One room is bigger and should carry more rent. When the app can't tell the difference, roommates sort it out manually, and that's where arguments start. Fair Share removes both problems: the friction of logging, and the unfairness of equal splitting. How it works: Setup takes under a minute — name the flat, pick a currency, add roommates. In Settings, configure the flat's shared infrastructure: electricity rate, tariff status, per room AC specs, water rate, and gas rate. This configuration powers everything downstream. Logging an expense is as simple as talking. A flatmate sends a voice note: "I ran the AC for two hours," "bought groceries for 400 rupees," "we paid 6,000 for rent." Speechmatics transcribes it in real time, and Featherless AI classifies the expense as individual, shared, utility, or rent, logging it automatically with a timestamp. Shared costs like rent stay pending until other roommates confirm them, building a mutually agreed, tamper evident record instead of a memory based dispute. At month end, instead of dividing the total evenly, Fair Share computes a usage weighted split, factoring in AC tonnage, hours run, room rent weight, and utility rates, to show what each roommate actually owes, plus a clear "who owes whom" settlement figure. Why it matters: Fair Share is a fairness engine for shared living. By pairing near zero effort voice capture with usage aware billing, it solves the two reasons roommate expense tools fail: nobody wants to type, and nobody trusts an equal split when usage isn't equal.
10 Aug 2026
