The Future of Aviation Predictive Analytics – A Case Study

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 statistical modeling and integrating these models into the F-35 maintenance workflows.  Robert McCutcheon, Project Manager at ASI said, “AIPS leverages decades of supportability experience from ASI and the Machine Learning expertise from NLP Logix.” The Gnarly Problem ASI began development of an AI-powered aircraft maintenance application called AIPS. AIPS’s intention was to provide maintenance personnel with the optimal suggested actions to a given alert by on-board aircraft systems with the goal of reducing cost and maintenance time. The ASI and NLP Logix Teams worked [...]

July 12th, 2022|Categories: Artificial Intelligence, Case Studies, Predictive Modeling|0 Comments

Data Science Interns Journey

Intern's Journey Whether it’s teaching a class, presenting, or attending career fairs, NLP Logix team members are often found in the educational community. We are passionate about Data Science and work with area schools and universities to nurture future Developers, Engineers, Mathematicians, Analysts, and Operations team members.    To further support our culture of learning and development, college students are also frequently found at work in the NLP Logix office as paid interns.  In many cases, we find a great fit with an intern who joins our team full-time after graduation. Ted Willich, NLP Logix CEO states, “For those with a team mentality, who are ready to learn and contribute, the opportunities to expand their skills and experience is exciting to not only them but NLP Logix as well.”  Vince Duarte teaching Data Science Boot Camp Vince Duarte, currently studying Computer Science at the University of Florida, began his journey with NLP Logix in high school attending the NLP Logix Boot Camp.  The Boot Camp offers rising high school seniors the opportunity to solve analytics and machine learning problems for real world professional entities.  As Duarte’s interest in programming grew, and his university studies [...]

July 6th, 2022|Categories: Boot Camp, Internships|0 Comments

OCR vs. Data Capture Automation

What is the difference between OCR and AI/ML Data Capture? To put it simply, OCR recognizes text and follows simple commands.  AI/ML Powered Data Capture captures the intent of the document and reads the words. NLP Logix’ patented Data Capture Automation technology incorporates Natural Language Processing, Computer Vision, and Machine Learning to capture all the data in a document in context. This process interprets the data objectively, much the same way a human would.  Over time, Data Capture Automation can learn from it's mistakes and adapt to new content. Incorporating additional automation to your data extraction process can increase scalability, lessen the need for human interaction, and allow your staff to focus on more important tasks. Beyond just reading text Optical Character Recognition (OCR) is great at reading exact characters from a document, but data capture tasks require more than knowing the text on the page.  Data Capture Automation takes you the last mile.   At its core, Data Capture Automation utilizes OCR, but often incorporates steps before (pre-processing) or after (post-processing) to create results that solve business problems. Pre-processing algorithms are utilized to ensure that OCR can work optimally. [...]

Debunking Myths – Rethinking the Approach to Data

Debunking Myths - Rethinking the Approach to Data Since the inception of NLP Logix in 2011, clients have asked the team to solve an array of machine learning and automation challenges.  In the quest to unravel those challenges and provide client solutions the NLP Logix team has often defaulted to multiple lenses… meaning sometimes the obvious path requires a second look from a different perspective. Recently, our team was able to figure out a difficult issue by rethinking the approach to the data. Read on. Case in point, when working on a computer vision model the NLP Logix team was tasked with identifying malfunctioning pistons.  When the pistons were caught in the engaged position they were considered malfunctioning.  These faulty pistons were causing the client excess expenditures in gas and parts maintenance.    Using computer vision NLP Logix sought to identify the engaged pistons for the client. The obvious tell of the engaged piston was the positioning of the piston mechanism as a whole.  Annotated photos of engaged and disengaged photos were collected to train the predictive model.  Despite iterations, training predictions to spot the engaged pistons (model precision) were found inconsistent approximately  50% of the time.  It [...]

July 5th, 2022|Categories: Computer Vision, Modeling and Integration|0 Comments

Serious About Safety – Job Site Accident Probability

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 this analysis pushing it to the next level. “The first goal of this work was to get the buy-in from the men and women that work in the field,” Miller Electric, Vice President of Business Analytics Kerri Stewart said. “We did this by validating what they knew intuitively. If you ask anyone who works in the field why a safety incident has occurred, they could point to a number of factors that contributed. The first stages of work we did with NLP Logix validated their instincts. We [...]

May 11th, 2022|Categories: Assessments, Case Studies, Predictive Modeling|0 Comments

Debunking Myths – Is more data always better?

Is more data always better? More data isn’t always better.  Sometimes it’s just more.  Collecting large amounts of data without strategy can often create massive data set tangles to unravel.  Large data dumps tend to waste time and cause frustration if the information presented is not relevant. To avoid snags, smaller data sets can be utilized to effectively identify insights.    Over the past decade, Ben Webster, NLP Modeling and Analytics Team Lead, has seen a shift in how teams interact with data.  The question used to be:  “Do I have enough data?” Most companies were just at the point of sufficient data for machine learning tasks. The better question is: “Is the data relevant to the use case?”  Webster starts with an investigation of the use case to ensure that the data is capturing what is needed to support the use case (product or solution) and nothing more. This means filtering out bad or incomplete data, isolating recent data, and focusing only on data attributes that drive the use case.    Do you have questions about how to manage your data? Our 10Q Assessments are [...]

May 10th, 2022|Categories: Assessments, Data Science|Tags: , , |0 Comments

NLP Logix Joins NVIDIA Metropolis Partner Program

NLP Logix Joins NVIDIA Metropolis Partner Program NLP Logix, a leading machine learning and automation solution provider, today announced it has joined the NVIDIA Metropolis Partner Program, a program designed to nurture and bring to market a new generation of vision AI solutions to make processes more efficient. One of the challenging barriers facing any artificial intelligence/machine learning company is the ability to quickly gather large and accurate enough data sets to train a computer to do a task normally accomplished by a human. For example, if you wanted to train a computer to review hours upon hours of video, and accurately identify specific items such as a stop sign, light post, item in a crowd etc., you would have to gather the data, review it and note (annotate) enough positive examples and then feed the results through specialized hardware to be able to train the computer to accurately identify the items in future video. “This computer vision algorithm training pipeline has not changed much over the past ten plus years that we have been doing this at NLP Logix,” said Matt Berseth, Co-Founder and Chief Information Officer. “It has always been very time consuming [...]

March 14th, 2022|Categories: Computer Vision, Press Releases|0 Comments

RPA – How to Hire a Bot

Should your next new hire be a bot? Your employees are your most valuable resource. They set the tone and the personality of your organization. They will likely be the first to spot trends, anomalies, and errors. And they are the experts in how your company succeeds. When you value your employees, shouldn't you also value how they spend their time? Consider the repetitive tasks taking place in your organization... Downloading files, coding, matching, confirming, aggregating... Our Leadership Team is available to talk to you about Automation Let's Talk Scaling with Robotic Process Automation (RPA) Robotic Process Automation allows you to replace your team members' mundane and repetitive tasks with a bot, enabling them to focus their attention on the more important aspects of their roles, like complex decisions, critical analysis, and human interactions. Adding automation to their workflows allows them to oversee a much larger portion of their tasks quickly.  This in turn allows for faster upscaling or downscaling as the market dictates, and less mass hiring or layoffs. Learn more about RPA [...]

June 18th, 2021|Categories: Artificial Intelligence, Robotic Process Automation|0 Comments

Our Approach to Automation – Start Small

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. The advice we always give is - start small. Although you could probably think of dozens of automation opportunities, it's important not to try to do them all at once. Start with the low hanging fruit. Pick a use case that is relatively easy and could provide some immediate ROI. Think of things like repetitive clicks, basic data entry, uploading forms, etc. At NLP Logix, we always recommend first doing an assessment of the entire organization's data, as the basis for an automation plan.  This gathering [...]

Fourth OCR Patent Awarded to NLP Logix

NLP Logix Awarded Fourth Patent for Industry Leading Application of Artificial Intelligence to Extract Data from Document Images Jacksonville, FL, February 16, 2021 Just about every organization in the world has large volumes of documents stored in a physical folder and/or in digital format in a data base in their server rooms or in the cloud. These documents represent years of hard work by the employees who produced them, as well as a large financial investment made by the organization. The challenge for organizations has been how to automate classifying and extracting pertinent information from all the different document types. The most current optical character recognition (OCR) technologies fall well short of being able to do this effectively. Learn more about Data Capture Automation Data Capture Automation To solve this challenge, the award-winning data science team at NLP Logix repurposed a neural network algorithm it used to accurately identify breast cancer tumors in pathology slides. The team then trained the algorithm to identify and extract characters and other features from document images, such as a logo. The end-to-end process to accomplish this complex task generally follows this workflow: collect large [...]

February 16th, 2021|Categories: Data Capture, Data Extraction, OCR/ICR, Press Releases|0 Comments

Innovation and Automation in Data Extraction

Automation in Data Extraction How quickly can you respond to economic fluctuations? Does your volume fluctuate? One thing we learned in 2020 was that our predictions for our business volume was about as accurate as a flip of the coin.  Some businesses saw exponential growth, while others stagnated.  Many businesses learned hard lessons about being able to scale quickly and efficiently. If your industry is one that fluctuates with markets, seasons, or other variables, it is very difficult to hire, train, and maintain staff to manually process your data. It becomes crucial to find a solution that allows you to flex your current staff...not only can they skip the repetitive tasks, but they can focus on the complex tasks that require human interaction. With innovation and automation, you will free up time from those repetitive administrative tasks, allowing your team to dedicate time to more strategic planning and other high value projects, like interpreting and analyzing your data. Additionally, with the right data process automation model in place, the difficult job of hiring, training, or laying off of employees is minimized when scaling up or down. The NLP Logix solution Using [...]

February 3rd, 2021|Categories: Artificial Intelligence, Data Capture|Tags: , |0 Comments

Education Savings Account Platform

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 exponential growth in demand. "Even before COVID we were expecting to grow from administering $700m in scholarships to over $1b. But now, families are having to supplement their children’s education at home and/or through neighborhood pods, which has increased the need for parents to have access to more scholarship funds, and more flexibility in how these funds are spent." Doug Tuthill, President, Step Up For Students To support their mission and growth, Step Up For Students has turned to NLP Logix, a Jacksonville, Florida-based machine [...]

The COVID-19 Butterfly Effect

The COVID-19 Butterfly Effect Without question, COVID-19 has had massive effects on data. There are obvious changes that we see reported in the news – hospital revenues down, commercial air travel is down, etc. But each of those changes can create longer term changes in the data that analyst and data scientists will rely on in the future. In this blog, we will review the COVID-19 “Butterfly Effect” and how we can “cure” our COVID-19 data woes.   The COVID-19 Butterfly Effect Almost daily we see stories around the effect of coronavirus in hospitals. ERs and ICUs are full of patients. But with the increase in coronavirus cases, we also see a decrease in the volumes of other departments. From cancellations of elective surgeries to patient’s fears around going to the office, these changes in volume can have long standing effects. Large organizations depend on volume and revenue forecasting for everything from staffing to budgeting. Additionally, from a clinical perspective, we could see additional need for hospitalization in the future due to delayed preventative or maintenance care. These delays in care could also cause changes in how we measure disease progression and mortality.   Another hard-hit industry has been commercial air travel. Beginning with shutdowns and continuing with most consumers avoiding [...]

November 20th, 2020|Categories: Analytics, Data Science, Predictive Modeling|Tags: , , |0 Comments

Making the Most of Your Collection Attempts – CFPB Rule

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 are staying compliant and still making effective calls?   The answer is Artificial Intelligence. For over 5 years, NLP Logix has been building machine learning models to help agencies prioritize and segment their portfolios.  One of the outputs of the ML models is to recommend the best time of day to make a call. There are several factors to consider – where is the consumer located, what kinds of phone numbers do you have for the consumer, and how many different numbers are tied [...]

Is there a better way to handle bad debt scoring?

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 for predicting consumer behavior for paying debt. Which is more predictive? If you were to prioritize your entire portfolio of bad debt accounts by their credit score, you would find that those at the top of your list would be the ones with higher credit scores and visa versa.  This has been how most collection firms have operated for years, and for the most part this strategy works. A credit score is good at determining who can pay but not who will pay. The credit score does [...]

October 21st, 2020|Categories: Artificial Intelligence, Collections, Machine Learning, Predictive Modeling|Tags: , , , , , |Comments Off on Is there a better way to handle bad debt scoring?
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