Today, I focused on improving the backend of Nexa AI. I worked on connecting the different parts of the system, including: - Career recommendations - Skill gap analysis - CV feedback - Job readiness evaluation - Personalized career reports One of the biggest lessons from building AI applications is that creating the workflow behind the scenes is just as important as the final interface. #AgenticAI #AICommunity #GenerativeAI

I had the privilege of attending a recent session with DDS AI and learned so much about thinking about your product when working with AI, Agentic AI vs RAG, Prompt Engineering, and using the appropriate language model for your use case. One major insight was that when building with AI you want to start with a real problem you are trying to solve instead of picking the latest and greatest model or trying to make another chatbot. We discussed how Agentic AI is capable of reasoning, using tools, having a memory, and acting on a plan. While RAG allows your AI to connect with verified documents to create more grounded answers. I’m also learning the hard way how important it is to just try things out, be your own user when testing, write down what works, and iterate. Just because one model performed better for one task doesn’t mean they will for another task. Select your model based on what the user needs and what your project requires. I’m an Electrical Engineering student, and these are lessons I will take with me as I start to brainstorm for my senior design project. I’ve been working on an idea for a while now. It’s an AI called CampusMate, an intelligent university assistant to help students keep track of classes, search academic documents, and plan their semester. Thanks to Decoding Data Science and the DDS Business Circle, the mentors that lead the sessions, and the AI community as a whole. I can’t wait to learn more, try new things, build, reflect on my successes and failures, and share my journey. #DDSNextGen #DDSAmbassador #DecodingDataScience #DDSBusinessCircle #AgenticAI #ArtificialIntelligence

Today I improved Nexa AI’s agent system. What I worked on: ✅ Career matching improvements ✅ Skill gap analysis ✅ Job readiness recommendations ✅ Personalized learning roadmaps ✅ Career-based project suggestions Nexa AI can now analyze a user profile and provide a more personalized career plan instead of giving generic advice. Continuing to improve the agent workflow and make Nexa smarter every day! 🔥 #AgenticAI #AIChallenge

Introducing Lumen AI — an AI-powered Dubai Utility Bill & Energy Assistant, built during the DDS Enterprise AI Bootcamp by Decoding Data Science. The problem it solves: Understanding a DEWA bill isn't easy. Electricity slabs, water charges, fuel surcharge, housing fee, sewerage fee, and VAT can make it confusing—especially for new residents. Lumen AI explains bills in plain language and provides accurate estimates using official DEWA tariff information. You can ask it: 🔹 "Why did my DEWA bill increase this month?" 🔹 "Estimate my bill for 3,500 kWh." 🔹 "How do electricity slab rates work?" 🔹 "How can I reduce my monthly energy bill?" Tech Stack ⚙️ LlamaIndex (RAG)📦 Pinecone🤖 OpenAI GPT-4o-mini 🌐 @Flask 🐳 Docker, Inc 🤗 Hugging Face Spaces What I learned ✅ Better data beats bigger models. ✅ RAG quality depends on the knowledge base. ✅ Building and deploying a real AI product is the best way to learn. 🚀 Live Demo: https://huggingface.co/spaces/nipunkavindaAI/LumenAI 💻 GitHub: https://github.com/NipunKavinda95/LumenAI Thanks to Mohammad Arshad and Decoding Data Science for another hands-on learning experience. DDS Business Circle Dubai Electricity & Water Authority - DEWA #AI #GenerativeAI #RAG #LlamaIndex #OpenAI #Pinecone #HuggingFace #DEWA #Dubai #BuildWithAI #DecodingDataScience #LearningInPublic

Pleased to share my dss chatbot which I made during July bootcamp https://03848a2eb9773d4f94.gradio.live/