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Schedule Interview NowAt Softaims, I’ve found a workplace that thrives on collaboration and purposeful creation. The work we do here is about more than technology—it’s about transforming ideas into results that matter. Every project brings a mix of challenges and opportunities, and I approach them with a mindset of continuous learning and improvement. My philosophy centers around three principles: clarity, sustainability, and impact. Clarity means designing systems that are understandable, adaptable, and easy to maintain. Sustainability is about building with the future in mind, ensuring that the work we do today can evolve gracefully over time. And impact means creating something that genuinely improves how people work, connect, or experience the world. One of the most rewarding aspects of working at Softaims is the diversity of thought that every team member brings. We share insights, question assumptions, and push each other to think differently. It’s this culture of curiosity and openness that drives the quality of what we produce. Every solution we deliver is a reflection of that shared dedication. I’m proud to contribute to projects that not only meet client expectations but also exceed them through thoughtful execution and attention to detail. As I continue to grow in this journey, I remain focused on delivering meaningful outcomes that align technology with purpose.
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Developed an intelligent, voice-enabled Linux agent that connects to remote Linux servers and executes commands based on natural language input. Users can interact with the system via text or speech, describing tasks in plain English (e.g., "check disk usage", "create a new user", "restart nginx"), which are then interpreted, validated, and securely executed on the target server. The system supports: Real-time connection to Linux servers over SSH Parsing and mapping natural language to shell commands Voice-to-text input using speech recognition Execution monitoring and result feedback
Developed and fine-tuned a MobileNetV2 convolutional neural network (CNN) to classify rice grains into five distinct categories. The model was trained on a labeled dataset and deployed using a GPU server to accelerate the training process. Achieved high classification accuracy with optimized model size suitable for edge or mobile deployment.
AI Invoice Agent is a modern web-based solution built with Next.js and powered by LLM for automating invoice data extraction. It allows users to drag and drop PDF, JPG, or PNG invoices, which are parsed in real-time to extract structured fields like invoice number, date, vendor, customer, items, and total amount. The extracted data from multiple invoices is compiled into a single downloadable Excel file for accounting and record-keeping. 📈 Outcome ✅ Reduced Manual Work: Saves hours of manual data entry ✅ High Accuracy: AI provides accurate field extraction from scanned or digital invoices
Bachelor of Computer Science (BCompSc) in Computer engineering
2020-01-01-2024-01-01