There is a significant backlog of legal proceedings in several large countries, including India. There have been technical advancements in intelligent devices that can process and summarize legal documents. However, developing such data-driven systems requires a scarcity of high-quality corpora. Legal AI focuses on using artificial intelligence technology, particularly Natural Language Processing (NLP), to help with legal duties. Legal professionals frequently consider how to solve problems using rule-and symbol-based methods, but NLP researchers are more interested in data-driven and embedding methods. So, in this paper, we present Indian Legal Corpus (ILC), a dataset for Indian legal document summarization. Our dataset differs from the existing summarization datasets in a way that our summaries are highly abstractive. This dataset offers new research opportunities for Legal documents with an abstractive approach. ILC is highly abstractive, concise, and of high quality, as indicated by human and intrinsic evaluation. We are releasing our dataset and models to encourage future research on Legal abstractive summarization.