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Misbah Syed@Misbah
is under improvement
6
Events attended
3
Submissions made
Founder - Menlo Park Lab
Canada
4 years of experience
About me
I have worked as a Data Scientist and an MLE since 2019, and have deployed many different ML models to production. I have worked primarily with time series data, and deployed ML applications for manufacturing, saving over $2 million per year in manufacturing waste. I have also helped build infrastructure for ML deployment used in healthcare applications. Currently, exploring building AI-based companies.
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🤓 Submissions
Chatty Panda
Chatty Panda is an artificial intelligence-powered tool that enables businesses to provide efficient and effective support to their customers. This chatbot is designed to handle customer queries related to business policies, documents, and other important information in multiple languages. The chatbot is programmed with a company-specific database of information related to business policies, regulations, and documents, which allows it to provide accurate and helpful responses to customer inquiries. With its multilingual capabilities, the chatbot can cater to customers from different parts of the world who speak various languages. Customers can interact with the chatbot through a user-friendly interface and ask questions related to their concerns about company policies. The chatbot uses natural language processing to understand the queries and provides relevant answers in real-time. The multilingual customer representative chatbot is a cost-effective solution for businesses looking to improve customer support and streamline their operations. It reduces the workload of customer service representatives and ensures that customers receive quick and accurate responses to their queries, ultimately leading to higher customer satisfaction and loyalty.
Ask Quran
Our goal is to develop a system that can take documents in any language and allow users from different parts of the world with different languages to interact with those documents. This can help spread knowledge without any language barrier. We are first testing it out with Quranic text, which is in Arabic, and building a chatGPT-style bot for question answering. In future, we would like to expand it to additional documents in any language. We first perform embedding of the text using Cohere's multilingual embed model and save those embeddings in a vector database, Pinecone DB in our case. We then take user queries and also embed them and perform a similarity-based search to provide the most relevant results based on the query. The app is currently deployed and publicly available. Streamlit app link: https://taqihaider7-tafsir-quran-sementic-search-llm-app-fwh2if.streamlit.app/
AI Brand Intel
Our platform provides businesses with the ability to monitor and analyze social media and news mentions in over 100 languages, all in one place. With our language translation and content intelligence solution, businesses can easily generate responses in their customers' preferred language, stay on top of industry news and trends, and streamline their content management process. Our platform allows businesses to upload their policies and internal documents in over 100 languages, generating chatbots and semantic search engines that enhance customer experience and streamline content management. We are utilizing cohere multilingual embeddings and Qdrant vector DB to generate and save embeddings. A flask-based api backend and a bubble.io based no-code front-end is used to build the solution.
