Sarvaha has over eight years of experience building semantically intelligent applications for analyzing large, heterogeneous datasets. We leverage NLP, machine learning models, and ontologies to solve complex enterprise problems, and build scalable search-driven systems using distributed processing frameworks such as Hadoop, NoSQL databases like MongoDB, and search platforms including Lucene and Elasticsearch. Our expertise spans open-source text mining and ML tools such as Stanford NLP, Apache Mahout, and Jena, with strong capabilities in data curation, feature engineering, and performance-focused visualization. We have delivered solutions such as automotive repair intelligence platforms that analyze large volumes of historical data to provide predictive operational and strategic insights, as well as information retrieval systems supporting cancer research at a leading university. We complement analytics with intuitive, high-impact visualizations built using modern JavaScript visualization libraries.