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Databricks Partnership

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Databricks Partnership

2022-10-03T13:32:37+00:00October 3rd, 2022|Categories: Artificial Intelligence, Assessments, Data Extraction, Data Science, In the press, Machine Learning, Partnership, Press Releases|

Databricks Drives Business Value Machine learning services built on Databricks’ Lakehouse Platform provide expedited value to clients to solve their big data problems. NLP Logix, one of the fastest growing custom machine learning/artificial intelligence companies in the United States, today announced they have partnered with Databricks, the lakehouse company, to drive business value by unifying data and artificial intelligence (AI).  NLP Logix brings over a dozen years of experience in developing and deploying custom machine learning and business automation solutions across multiple industries including defense, human resources, non-profit, financial services and others. "At NLP Logix we say that "Data Science [...]

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Uncertain Market

Benefits of Automation in an Uncertain Market

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Benefits of Automation in an Uncertain Market

2022-08-31T19:12:22+00:00July 29th, 2022|Categories: Artificial Intelligence, Automation, Machine Learning|Tags: , , , , , , |

Benefits of Automation in an Uncertain Market With discussion of an economic downturn on the rise, the days ahead may seem as unsteady as walking a tightrope with the consequences leaving many performers asking if the safety net is secure and what other checks are in place? Pivoting to find balance, organizations are turning to the benefits of Robotic Process Automation.   Many organizations have already found early success in automating redundant but necessary tasks such as data entry, document processing, medical coding, as well as other time-consuming areas of their operations.  These types of projects are often the first steps in an organization’s RPA journey as these types [...]

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task automation

Our Approach to Automation – Start Small

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Our Approach to Automation – Start Small

2022-07-20T19:55:37+00:00March 20th, 2021|Categories: Analytics, Artificial Intelligence, Automation, Machine Learning, Natural Language Processing, Predictive Modeling|Tags: , , , , , |

Our Approach to Automation - Start Small Automation to compensate for an employee shortage Help Wanted!  Signs are up everywhere, as employers are building their production back up. But finding qualified employees is difficult right now.  Are you spending time trying to figure out how to accomplish more, with less staff? Regardless of the industry you are in, this is a great time to look into automation through AI/ML. Where do I start with the Automation process? One of the most common questions we get from clients is where to even get started as that task can often seem daunting. [...]

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Education Savings Account Platform

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Education Savings Account Platform

2022-07-22T18:20:22+00:00December 21st, 2020|Categories: Artificial Intelligence, Machine Learning, Press Releases|Tags: , , , |

Step Up For Students Selects NLP Logix to Build Education Savings Account Platform Rapid expansion of education savings accounts, which empower parents and students to choose their education resources, requires a platform to streamline and provide visibility on how funds are spent. Step Up For Students was founded to empower families to pursue and engage in the most appropriate learning options for their children, with an emphasis on families who lack the information and financial resources to access these options. Over the years, Step Up For Students has developed internal systems and procedures to administer these scholarships, which disproportionally benefit minority children and families, but now they are expecting [...]

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Making the Most of Your Collection Attempts – CFPB Rule

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Making the Most of Your Collection Attempts – CFPB Rule

2022-07-22T18:40:51+00:00November 3rd, 2020|Categories: Automation, Collections, Machine Learning, Predictive Modeling|Tags: , , , , |

Make your attempts count - How Machine Learning models can help with the new CFPB rule The CFPB recently released a new rule that limits contact attempts to only 7 per week per consumer. Maintaining and improving Right Party Contact (RPC) rates is now more important than ever! This means that you not only have to call the right number, but you have to do it at the right time. The rule will have many agencies scrambling to figure out a way to make the most of their calling strategies to keep their collections rates from dropping. How will agencies ensure they [...]

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Collection Scoring Model

Is there a better way to handle bad debt scoring?

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Is there a better way to handle bad debt scoring?

2021-01-20T15:12:09+00:00October 21st, 2020|Categories: Artificial Intelligence, Collections, Machine Learning, Predictive Modeling|Tags: , , , , , |

Despite the current financial crisis, credit scores are soaring – Is there a better way to handle bad debt scoring? For many years, credit scores have been the primary tool used to prioritize bad debt accounts for the vast majority of collections agencies.  For the most part, a person’s credit score is a good indicator to determine if they are capable of paying back their debt.  But with advances in AI technology and with the average consumer credit score reaching new highs, (see WSJ article here) should agencies be looking at alternative ways to prioritize their accounts? In this article, we’ll compare traditional credit scores to machine learning models as a strategy [...]

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Collection Scoring with AI/ML

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Collection Scoring with AI/ML

2022-07-27T15:44:00+00:00October 9th, 2020|Categories: Artificial Intelligence, Collections, Machine Learning, Predictive Modeling|Tags: , , , |

Collection Scoring - How Healthcare Providers Can Use AI/ML for Optimal Results Debt collection is a costly, yet necessary undertaking for healthcare providers. To reduce costs, debt collection often gets outsourced to a third-party agency. However, handling accounts that are more likely to pay in-house can reduce outsourcing costs. To accurately identify these accounts, healthcare providers can leverage artificial intelligence (AI) for Collection Scoring. Why Healthcare Providers Should Use AI For Collection Scoring AI-based collection scoring models allow healthcare providers to accurately determine which accounts receivable to handle in-house and which to outsource to collection agencies. This results in: Increased debt collection rates, because collectors will [...]

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How Innovative is Your Company?

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How Innovative is Your Company?

2022-07-22T19:08:29+00:00September 21st, 2020|Categories: Artificial Intelligence, Automation, Data Science, Machine Learning|Tags: , , , , , |

The interest in AI and automation has continued to rise in recent years and is expanding into almost every department for both small and large organizations.

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QuantHub Partnership

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QuantHub Partnership

2021-08-06T13:28:17+00:00September 1st, 2020|Categories: Artificial Intelligence, Automation, Machine Learning, Partnership, Press Releases|Tags: , , , , , |

NLP Logix & QuantHub Partnership Announcement   NLP Logix is pleased to announce a new partnership with QuantHub, a leading data science skills assessment and development platform, to offer complete Machine Learning/AI solutions.   QuantHub's strengths are in empowering companies to build the technology teams they need to be able to support and improve upon the ML/AI programs they have in place. NLP Logix's strengths are in putting those ML/AI programs in place. Combined, we can offer a complete solution.   The Process     NLP Logix offers the customized Machine Learning and Artificial Intelligence solutions you need to scale your business automation. From the initial steps of identifying your challenges all [...]

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The Challenges of Machine Learning Models

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The Challenges of Machine Learning Models

2022-08-11T20:14:29+00:00August 14th, 2020|Categories: Data Science, Machine Learning, Workflow|Tags: , , |

The challenges of Machine Learning models Machine Learning models are becoming increasingly more popular as data science teams are finding new ways to apply these models across a variety of industries and use cases.  From predicting outcomes such as how fast a wound will heal to training a model to read and extract text from documents, ML models can be applied to almost any use case provided the right data is available.     Much of the heavy lifting when building ML models happens in the early stages of gathering and understanding data, modeling the data and training the model.  However, actually putting the model into production has its own [...]

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