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The Fire Watch – A Case Study

2022-08-31T15:47:30+00:00August 31st, 2022|Categories: Analytics, Case Studies, Data Science|

Mission Fire Watch Background Context The Fire Watch is dedicated to ending veteran suicide in the State of Florida.  According to The Fire Watch, "Veteran suicide is a growing crisis. At least twenty U.S. veterans are taking their lives every day. To date, solutions to prevent suicide have been inadequate at best. In particular, federal solutions have had little to no effect on the crisis on the ground here in Florida. Given that Florida is home to over 1.5 million veterans, the need and the challenge are evident.”  To support its mission, The Fire Watch engaged NLP Logix in 2021 to gather, extract, transform and load disparate data [...]

The Future of Aviation Predictive Analytics – A Case Study

2022-08-31T15:53:52+00:00July 12th, 2022|Categories: Artificial Intelligence, Case Studies, Predictive Modeling|

Andromeda - The Future of Aviation Predictive Analytics A Case Study Background Context In 2019, NLP Logix partnered with Andromeda Systems Inc. (ASI) the leader in Department of Defense and commercial supportability to enhance maintenance of the military’s F-35 fleet of the Lockheed Martin single-seat, single-engine, stealth multirole fighter aircraft.  The program intended to optimize unscheduled maintenance of the F-35. This project began as ASI focused on the next generation of an existing initiative called Artificial Intelligence Prognostic Steering™ (AIPS), designed to enhance high-end transportation machinery, such as the F-35 operation and performance. The next evolution of AIPS was transformed by utilizing a combination of machine learning and [...]

Serious About Safety – Job Site Accident Probability

2022-07-05T18:28:48+00:00May 11th, 2022|Categories: Assessments, Case Studies, Predictive Modeling|

Always Serious About Safety - Job Site Accident Probability A Case Study with Miller Electric Company, Jacksonville, FL Background Context In 2021, NLP Logix client Miller Electric sought to develop a method to better understand how to leverage their extensive data to identify safety related opportunities and drive awareness of the underlying factors that could lead to safety issues. In support of this initiative, Miller Electric and NLP Logix engaged in several discovery workshops as part of NLP Logix’s 10Q Assessment methodology where questions were posed with a focus on understanding underlying trends in reported injuries. Safety Culture has always been a priority at Miller Electric with [...]

The State of AI 2020

2022-08-11T20:00:54+00:00August 20th, 2020|Categories: Artificial Intelligence, Automation, Case Studies|Tags: , , , , |

      The State of AI 2020   Survey Results   We sent out a survey to approximately 5000 business professionals from a variety of positions and industries and asked them a few questions about the current state of Artificial Intelligence (AI) as it relates to their industry. We have received and compiled the results into our report "The State of AI 2020". Click to download this free report and see how your organization compares. Survey Results - Download Now     Learn More…   To learn more about these survey results, or to discuss AI or automation projects within your own organization, contact us:(904) 208-5065           [...]

Deep Learning Data Extraction Technique – NLP Logix Awarded 3rd Patent

2022-08-17T18:46:34+00:00June 9th, 2020|Categories: Artificial Intelligence, Case Studies, Data Capture, Data Science, Deep Learning, Press Releases|Tags: , , , , |

Neural Network-based algorithm that was originally trained to identify breast cancer tumors on pathology slides, re-purposed to classify and extract data from document images with Deep Learning Data Extraction.   Jacksonville, FL - In late 2015, NLP Logix Lead Data Scientist, Matt Berseth, entered the company into the Camelyon16 Grand Challenge. The Camelyon16 was a challenge for the medical and computer science communities to come together to train a computer to identify breast cancer tumors, at a level at or above the highest trained pathologists in the world.  In April 2016, the top five winners were announced, with the combination team of Harvard Medical School and MIT taking first place, and [...]

AI/ML Top 5 Lessons Learned from Our Past Failures

2021-03-15T18:31:57+00:00May 21st, 2020|Categories: Analytics, Artificial Intelligence, Case Studies, Machine Learning|Tags: , , , |

Over the last 9 years, we’ve worked on hundreds of AI/ML projects with our clients.  The vast majority of these projects turned out to be very successful, but we have certainly made mistakes along the way.  Lots of them.  We’ve learned from every one of these mistakes so we don’t do it again. From issues with the data, API’s, building ML models and getting them into production, we’ve messed up.   However, over time, these lessons are invaluable in our success in delivering value to our clients.  Quite simply, we’ve already made the mistakes so our clients don’t have to. Here are our Top 5 Lessons Learned over the years. 1. Data Issues [...]

Weighing the Options: In House Vs Outsourcing Automation Programs

2021-03-15T18:33:03+00:00April 29th, 2020|Categories: Artificial Intelligence, Automation, Case Studies, Data Science, Machine Learning, Workflow|Tags: , , , , , , |

Are you considering using an in-house team of Data Scientists to implement an Automation program? Before you make your decision, consider the following criteria. Over the last 9 years, the team here at NLP Logix has developed hundreds of AI/ML solutions throughout a wide variety of industries.  From building predictive maintenance models for the F-35 to detecting breast cancer tumors in pathology slides, we have seen a lot when it comes to AI and automation. Often times we have clients who are debating whether or not to hire an outside firm such as NLP Logix, or build these solutions in-house by hiring an internal data science team.  The answer to that question [...]

Document Processing – Case Study Series

2022-08-17T17:06:57+00:00April 28th, 2020|Categories: Automation, Case Studies, Data Capture, Natural Language Processing|Tags: , , , , |

Automated Document Processing Pipeline   Focus on Scribe Fusion   Performance Matters. The Scribe Fusion technology allows for the processing of large volumes of paper documents with a mixture of OCR/ICR and artificial intelligence to interpret documents in much the same way humans do. This novel approach has led to drastic improvements in the data capture accuracy rates and scalability. With NLP Logix's Scribe Fusion™, our technologies were developed by an award-winning team of deep learning experts. We move beyond deploying out-of-the-box OCR/ICR software using artificial intelligence to interpret documents in much the same way humans do. We help our clients achieve levels of accuracy that are not possible with existing data [...]

5 Tips for Applying Automation to Your Recruiting Process

2021-01-18T15:24:24+00:00April 15th, 2020|Categories: Artificial Intelligence, Automation, Business Process Management, Case Studies, Matchpoint, Workflow|Tags: , , , |

5 Tips for Applying Automation to Your Recruiting Process   It seems that there are new products entering in the HR Tech space almost every day.  For a long time, most staffing and recruiting teams heavily relied on their Applicant Tracking System (ATS) to manage much of their day to day operations.  The leading Applicant Tracking Systems continue to add more features and functionality, however in recent years, many new recruiting technologies have emerged that promise new and improved ways to recruit and manage your staffing business.  Many of these new products include some form of A.I. or automation.      Applying automation to your recruiting workflows can sound like a daunting [...]

How A.I. Can Improve a Recruiter’s Productivity

2021-01-24T14:26:50+00:00April 10th, 2020|Categories: Artificial Intelligence, Automation, Case Studies, Matchpoint, Natural Language Processing|Tags: , , , , , |

How A.I. Can Improve a Recruiter's Productivity Although the technology behind A.I. continues to make advancements, the main purpose behind these solutions is still the same.  Automation is the key driver behind most AI/ML projects.  The ability to teach a computer how to perform time-consuming, tedious and repetitive tasks not only increases efficiencies, but decreases labor costs. The staffing and recruiting industry has begun to embrace AI as a way to improve operations and drive more placements.  Major advancements in Natural Language Processing (NLP) have allowed firms to automate a majority of the time spent in screening, matching and engaging candidates, which frees up more of a recruiter’s time.  This allows recruiters [...]

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