Native Teams
Native Teams is an all-in-one work payments platform trusted by over 3,000 businesses to manage international teams across more than 85 countries without requiring local legal entities. By automating global payroll, tax compliance, and contracting processes, we enable companies to scale their workforce efficiently while minimising legal risks.
Our array of services combines hands-on compliance expertise and a user-friendly platform that has everything needed for global expansion. Here’s an overview of our core services:
• Employer of Record (EOR): Through our legal entities worldwide, we process contracts, payroll, taxes, and social security and ensure full compliance with local regulations.
• Gig Pay: This service provides streamlined payment processing for gig workers worldwide, enabling fast, secure, and compliant invoicing and payments in multiple currencies.
• Entity Management: We assist companies in legally establishing local entities and maintaining ongoing regulatory compliance, reducing administrative burdens when entering new markets.
• Contractor Pay: We handle contractor payments across borders with multi-currency support and automatic tax compliance, simplifying the complexities of managing global gig talent.
• Contractor of Record: Native Teams assumes responsibility for contractors' legal and contractual obligations, ensuring compliance with local laws while reducing liability for client companies.
• Relocation services: For clients on the EOR plan, Native Teams offers support with visa applications and work permits to facilitate employee relocation and global mobility.
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Qloo
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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AWS Entity Resolution
Establish entity resolution workflows in just minutes instead of taking months to finalize. Set up sophisticated matching techniques tailored to enhance data accuracy according to your specific business requirements. Safeguard your data and limit its transfer by accessing records at their source. AWS Entity Resolution enables you to identify and connect related records without the necessity of creating custom solutions. Leverage adaptable, customizable machine learning (ML) and rule-based methods to fine-tune record matching based on your business objectives. Eliminate duplicate records for more effective information analysis, prepare your data for artificial intelligence (AI) model training, and boost your overall business performance. By utilizing unified insights, you can deliver more pertinent experiences across your advertising and marketing efforts, customer support interactions, loyalty programs, and ecommerce activities. Additionally, link SKUs, UPCs, or proprietary product identifiers into a cohesive product record to enhance tracking across various stores and supply chains, fostering a more integrated approach to inventory management. Ultimately, this streamlined process not only enhances data integrity but also drives strategic decision-making across your organization.
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NetOwl NameMatcher
NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.
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