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

CoComply是一家总部位于英国的工人分类SME，其核心项目团队由迈克尔·克利弗利(连续企业家/首席执行官/解决方案负责人)、乔·约翰逊(CILEx工人地位专家)和迈克·特纳(首席工程师AI/ML开发人员)组成。确保遵守工人分类对企业和政府来说都是一个具有挑战性的世界性问题。不正确的分类可能会导致各种负面后果，如收入损失、声誉受损、负债以及对自由职业者和创业型经济的伤害。2017年和2021年，英国政府推出了第10章IR35立法，将确定承包商纳税状况的责任转移到最终客户身上。在公共部门，对违规行为的处罚已超过3亿GB，私营部门的执法仍在继续。为了应对这一挑战，CoComply正在开发一个具有人工监督的AI/ML平台，该平台管理工资外工人的状态并定期评估角色状态以确保准确性。CoComply满足了对全面工人分类系统的日益增长的需求，该系统提供公正的评估和持续的合规管理。这种与技术无关的解决方案比传统的律师事务所或咨询公司更实惠。CoComply的解决方案快速而准确地确定工人的分类。与其市场竞争对手相比，该解决方案的成本效率超过81%，包括确保准确性的持续检查。通过使用CoComply，一个拥有100名承包商和22%未确定状态的组织通过CEST每年可以节省高达160万GB的成本，考虑到时间效率、风险避免和其他细微差别和衡量标准，这一节省要多得多。

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.