哈维尔·加西亚·德·莱尼兹

我训练和开发的NLP模型, 提取, and structure data from veterinary 发票 to allow for the reimbursement of animal health insurance claims.

我开发了一个由光学字符识别组成的管道, 布局检测技术, and named-entity recognition (NER) models to 提取 the relevant information from the 发票 accurately. I also built the validation module to identify and validate medical diagnoses against the policyholder coverage.
最后, I developed the 提取ion confidence methodology to help determine claims reimbursements to be processed automatically or reviewed by a human, 取决于不同模型的置信度和业务规则.

我训练和开发的NLP模型 key data points from mortgage 合同 to allow automatic audit and validation of data in actual 合同 vs the ERP.

I 训练有素的 a model to classify between main 合同 and their annexes, 扩展, 以及使用TF-IDF特征来训练分类器的修改. I also developed the validation module to disambiguate and match 合同 and DB rows and perform the comparison to highlight differences.

NLP models that I built and 训练有素的 to 提取 key data points from various 文档 such as 发票, 抵押贷款, 薪水, 和更多的.

The goal was to increase the efficiency of the application process for a tax relief program offered by the government due to COVID-19 that received millions of requests.

我开发了一个由手写文本检测组成的管道, 布局检测技术, 分类(检测文档类型), and NER (named-entity recognition) models to 提取 the relevant information from the 文档 accurately. I also developed the confidence module that prioritized manual review of applications based on business rules and models' confidence.

I developed an AI-driven system to automate the analysis of financial 文档 in construction processes, 针对大量的发票, 采购订单, 货物收到票据. This project aimed to detect mismatches and inconsistencies to prevent financial losses.

The project's pipeline started with 光学字符识别 technology to 提取 text from scanned 文档 accurately. I employed named-entity recognition (NER) models to identify and categorize key data points within these texts, 例如供应商名称, 日期, 和数量. An important part of the project was the development of classification models to accurately detect and categorize different document types, 自动检测其相关数据点.

另外, I implemented fuzzy matching algorithms to link items listed in 发票 with corresponding entries in 采购订单. This approach was key in identifying mismatches and inconsistencies.