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Schedule Interview NowAt Softaims, I have been fortunate to work in an environment that values creativity, precision, and long-term thinking. Each project presents a unique opportunity to transform abstract ideas into meaningful digital experiences that create real impact. I approach every challenge with curiosity and commitment, ensuring that every solution I design aligns not just with technical requirements, but also with human needs and business objectives. One of the most rewarding aspects of my journey here has been learning how to bridge the gap between innovation and practicality. I believe technology should simplify complexity, enhance efficiency, and empower people to do more with less friction. Whether building internal systems, optimizing workflows, or helping bring client visions to life, my focus remains on developing solutions that stand the test of time. Softaims has encouraged me to grow beyond coding—to think about design, communication, and sustainability in technology. I see every project as part of a larger ecosystem, where small details contribute to long-lasting results. My daily motivation comes from collaborating with people who share the same passion for doing meaningful work, and from seeing the tangible difference our efforts make for clients around the world. More than anything, I value the culture of learning and improvement that defines Softaims. It’s a place where ideas evolve through teamwork and constructive feedback. My goal is to continue refining my craft, exploring new approaches, and contributing to solutions that are not only efficient but also elegant in their simplicity.
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This AI-powered agent is designed to support TrainingPeaks (TP) athletes and coaches. It provides a chat-like interface that allows athletes to stay updated on their workout plans and receive personalized recommendations to enhance performance based on their TP data. For coaches, the platform includes a dedicated dashboard where they can manage athlete training plans, customize communication settings for each athlete, and create reusable message templates. The core objective is to streamline communication and planning for both athletes and coaches through intelligent automation.
I provided technical support to vistaBee to ensure operational continuity of their platform. I also led their development team to add new features, resolve critical bugs, improve security, optimize cloud cost, and ensure consistent DevOps practices. My key contributions included: 1. Provide daily technical support, add new features, resolve bugs 2. Document business processes 4. Enhance platform security 5. Optimize cloud infrastructure to reduce costs (helped reduce monthly cost from $9000 to $2500) 6. Improve DevOps workflows and code quality 7. Migrate existing data to a new platform
Agent Forge is a SaaS platform that lets you create, customize, and deploy AI-powered agents—chatbots, inbound call assistants, and website voice agents—without worrying about hosting, servers, or infrastructure. You bring your own services like Twilio, Deepgram, OpenAI, or other LLM APIs, and we take care of the rest. From hosting and storage to integrations and scaling, Agent Forge provides everything under one roof so you can focus on growth, not setup.
Manual scheduling is time-consuming, error-prone, and limited to business hours. This solution enables a 24/7 voice-based scheduling system that reduces workload for staff, minimizes booking errors, and improves customer experience by providing instant, voice-driven scheduling over the phone. It also captures valuable insights such as call summaries, recordings, and costs for analysis and logs these entries into Airtable Base.
Built a context-aware chatbot using a RAG Pipeline. The system processes a pdf documents, extracts text data, and generates semantic embeddings using a BERT-based model. These embeddings are stored in a FAISS vector store for efficient similarity-based retrieval. When a user submits a query, the chatbot retrieves semantically relevant passages from the vector store. It verifies context relevance, rewrites the query if needed, and passes the context to an LLM and uses chain-of-reasoning to generate a response. A final RAGASS check ensures the answer is grounded and not hallucinated.
Bachelor's degree in Computer science
2014-01-01-2018-01-01