An innovative Lawtech AI/ML platform with human oversight that manages off-payroll worker status and periodically assesses the role status to ensure accuracy.

具有人工监督功能的创新 Lawtech AI/ML 平台，可管理工资外员工的状态并定期评估角色状态以确保准确性。

• 批准号: 10099483
• 金额: $ 44.35万
• 依托单位: COCOMPLY LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10099483
• 关键词: innovative; Lawtech; AI; ML; platform

CoComply is a UK-based worker classification SME with a core project team of Michael Cleavely (Serial Entrepreneur/CEO/Solution Lead), Joe Johnson (CILEX expert in worker status) and Mike Turner (Lead Engineer AI/ML Developer).Ensuring compliance with worker classification is a challenging and worldwide concern for both businesses and governments. Incorrect classification can lead to various negative outcomes, such as revenue loss, damage to reputation, liabilities and harm to the freelance and entrepreneurial economies. In 2017 and 2021, the UK government introduced Chapter 10 IR35 legislation, which transfers the responsibility of determining contractors' tax status to the end client. Penalties for non-compliance have exceeded £300M in the public sector, with private sector enforcement still ongoing.To address this challenge, CoComply is developing an AI/ML platform with human oversight that manages off-payroll worker status and periodically assesses the role status to ensure accuracy.CoComply meets the growing demand for a comprehensive worker classification system that provides unbiased assessments and ongoing compliance management. This technology-agnostic solution is significantly more affordable than traditional law firms or consultancies. CoComply's solution determines worker classification quickly and accurately. The solution boasts a cost efficiency of over 81% compared to its market competitors, including ongoing checks to ensure accuracy. By using CoComply, an organisation with 100 contractors and a 22% undetermined status via CEST could save up to £1.6M annually and significantly more considering time efficiency, risk avoidance other nuances and metrics.

Cocomply是一个基于英国的工人分类中小型企业，由Michael Cleavely（串行企业家/CEO/解决方案负责人），Joe Johnson（Cilex Worker Stuce的专家）和Mike Turner（首席工程师AI/ML开发人员）。对工人分类的依从性是挑战，对企业和政府的关注是一个问题。不正确的分类会导致各种负面结果，例如收入损失，审查损失，负债以及对自由和企业家经济的伤害。在2017年和2021年，英国政府介绍了第10章IR35立法，该立法将确定承包商的税收状态的责任转移给了最终客户。在公共部门，对不合规的处罚超过了3亿英镑，私营部门的执法仍在进行中。为了应对这一挑战，Cocomply正在开发一个具有人类监督的AI/ML平台，该平台管理人类监督，管理非债务工人的地位，并定期评估角色状态以确保准确地符合不断增长的工人分类系统，以评估无数次数。这种技术不足的解决方案比传统的律师事务所或疑虑更实惠。 Cocomply的解决方案可以快速准确地确定工作人员分类。与市场竞争对手相比，该解决方案的成本效率超过81％，包括持续的支票以确保准确性。通过使用Cocomply，一个拥有100个承包商和22％未定地位的组织每年可以节省160万英镑，并且考虑到时间效率，风险避免其他细微差别和指标。