Tender Notice for Custom Bid for Services - TOTAL PRICE INCLUDING GST FOR COMPREHENSIVE DATA CLEANSING AND OPTIMIZATI in WEST DELHI, DELHI

The eligibility requirements for bidding on the comprehensive data cleansing and optimization service include being a registered entity with the proper authorities, showcasing proven experience in similar projects, and the ability to provide post-completion support as specified in the scope of work. It is essential to meet these criteria to ensure that your bid is considered during the evaluation process.

Bidders must demonstrate expertise in data management software and tools pertinent to data cleansing and optimization. The requirements also include established practices in maintaining data integrity and the ability to process large datasets efficiently. Providing examples of past work and methodologies planned for this project can strengthen your proposal.

The payment terms for this comprehensive data cleansing and optimization service will be specified within the tender documents. Generally, an Earnest Money Deposit (EMD) is required to show commitment to the bid, and details about the amount, conditions for refund, and processing will be outlined. Make sure to include clear financial particulars in your proposal.

Bidders are required to submit their proposals via the designated online platform as specified by GAIL India Limited. Typically, accepted document formats include PDF, Word documents, and any specified excel sheets that provide financial or technical details. Ensure all documents adhere to the submission guidelines outlined in the tender documentation.

Micro, Small, and Medium Enterprises (MSEs) can benefit from specific provisions within this tender, designed to encourage participation from smaller entities. These may include relaxed eligibility criteria, preferential treatment during the evaluation process, and potential training or support during execution. It's essential for MSEs to highlight these aspects in their proposals to maximize their participation likelihood.