Data Entry, Web Research, Data Conversion Services

About Data Entry, Web Research, Data Conversion Services

DataEntryIndia.in (DEI) is an India-based BPO specializing in data entry, web research, data conversion, and data quality services, claiming 25+ years of operating experience and a team of 850+ data experts across more than 1,200 completed projects. The service range is genuinely broad. On the data entry side, DEI covers CRM and Salesforce entry, handwritten and document data entry, invoice processing, insurance claims, legal documents, mortgage BPO, and medical data entry, among others. Their eCommerce practice handles product listing and catalog management across Amazon, eBay, Shopify, Magento, BigCommerce, and OpenCart. Web research services include data mining, web scraping, competitor profiling, business market research, academic and legal research, and social media research. Data quality work covers enrichment, deduplication, list building, email validation, LinkedIn data extraction, and cleansing. Data conversion covers PDF, XML, JATS, HTML, Word, Excel, and eBook formats. They also offer image and video annotation. The ISO certification claim appears on their homepage, though the specific standard isn't spelled out, I would ask them to confirm which ISO standard applies and request the certificate before treating this as verified compliance. DEI advertises US (+1 585) and UK (+44 203) phone numbers, which suggests at minimum some customer-facing infrastructure targeting those markets, though the actual delivery appears to be India-based. The client testimonials reference real estate, eCommerce, and healthcare-adjacent use cases, but no enterprise-level brand names are disclosed. Who is this a good fit for? Mid-size businesses, agencies, and digital publishers with high-volume, well-defined data tasks, catalog cleanup, web scraping, document conversion, list building, where cost efficiency matters and the work is repeatable and documentable. I'd want to confirm their QA process in detail: a claimed 99% accuracy rate is only meaningful if you understand the sampling method, error categories, and how rework is handled. Ask for a sample output and a pilot before committing volume.