Our Success Stories

CUSTOMER CHURN

Customer churn has created huge concerns in the highly competitive service sectors and especially in the telecom sector. The aim of this project was to build a customer churn model using AI (Artificial Intelligence) to predict whether certain customers would leave in the future. This helped the client to retain customers for the long run which improved revenues and business continuity.

WORKERS COMPENSATION FRAUD

Globally, workers compensation Insurance fraud has become a major concern for all the insurance companies which is continuously increasing year by year. The aim of this project was to build an AI model in order to rate the claims so that the SIU teams can process the cases according to the risk levels. This could lead to significant savings by eliminating fraudulent claims. This led to improved revenues and business continuity in the long term.

PREDICTIVE MAINTENANCE

The Client was a large Water Utility that needed to predict failure for their water pumps. AI Modes were generated for the equipment using historical data parameters for the pumps along with the past equipment downtime instances. Then, real-time equipment data was gathered from the remote equipment using IoT sensors and uploaded to our secure cloud.

HEALTHCARE INSURANCE

This case study is based on data from a large global insurance company which is engaged in providing health insurance. With offices in multiple countries, the claims department handles various activities such as processing and approving claims etc. Each of these processes comprise of several activities that are time consuming but critical for employee satisfaction. This solution leverages our Minsky™ AI engine to categorize each claim as High Risk or Low Risk based on the customers historical data. Minsky™ then creates accurate Modes that can be used to process live data for high risk/low risk to be handled by the appropriate claims adjuster based on the rating for further processing. This real time monitoring/actions helped us automate the claims processing across various geo locations offices while also reducing fraudulent claims. Solution was integrated with an existing system.

BRAIN TUMOR

Typically Brain tumor occurs due to uncontrolled and rapid growth of cells and could be fatal if not treated early. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. A major challenge for brain tumor detection arises from the variations in tumor location, shape, and size .And the first step in treatment for any brain tumor patient is often surgery to remove as much of the mass as possible and should not be delayed. The objective of this case study is to classify brain tumor through image segmentation from the MRI. Our approach was used to deliver comprehensive results using machine learning and deep learning algorithms on brain tumor detection through image segmentation magnetic resonance imaging combined with patient medical data. After a detailed analysis and research, Ai labs developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky™ to identify the presence of a tumor.

DISC BRAKE QUALITY INSPECTION

Typically for any manufacturing company, production quality and yield are two important performance metrics. Manufacturing processes typically include one or more steps where the product is visually inspected for defects. Typically, visual inspection is a highly manual process that can be time consuming and prone to errors. Poor production quality control results in significant operational and financial costs in the form of reworked parts, scrap generated, reduced yield, increased work in process inventory, post-sale recalls, warranty claims, and repairs. After a detailed analysis and research, Ai labs developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky™ to highlight the defects of casting product operations. The objective of this case study is to automate inspection process and identify the defects by categorizing them as (Defective, Pass) in the casting process using deep learning classification model.

FLEET MANAGEMENT

Typically, fleet management operations worldwide face major challenges to run successfully. They have high operating expenses and significant maintenance issues which can be detrimental to the business if not addressed properly in time. Sometimes, timely detection of an upstream problem such as engine failures can prevent more expensive downstream issues. Un-scheduled maintenance issues might disrupt Supply Chain deliveries. In order to address these challenges, companies are turning to Ai to avoid catastrophic failures in the fleet vehicles.

HYDROCEPHALUS

Hydrocephalus (HYC) is the segregation of fluid in the cavities (ventricles) deep within the brain. The excess fluid increases the size of the ventricles and puts pressure on the brain. Cerebrospinal fluid normally flows through the ventricles and bathes the brain and spinal column. Hydrocephalus is a frequent complication which is affecting almost all age groups following subarachnoid haemorrhage. Few studies investigated the association between laboratory parameters and shunt-dependent hydrocephalus. Non-contrast materialenhanced head computed tomographic (CT) examination is an important method for the diagnosis of HYC because it can observe the enlargement of the ventricles, and sometimes determine the cause of HYC. However, due to the lack of uniform standards, different range of patients’ ages and the various levels doctors’ expertise, it is rather difficult to reach a diagnosis. Therefore, after a detailed analysis and research, Ai labs developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky™ to highlight the need for a shunt for an individual and mortality caused by Hydrocephalus.

GLOBAL GHG EMISSIONS

Climate change has been a critical problem that requires rapid action in today’s Digital world to save our planet. Its impacts are already being felt globally and the negative effects are expected to grow exponentially, with disproportionate consequences for the world’s most marginalized communities. Tackling climate change requires action across society, spanning many communities, approaches, and tools. After a detailed analysis and research, Ai labs has done has developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky to highlight the effects of Climate change.

ULTRASOUND BREAST CANCER

Breast cancer is one of the most common causes of the death among women worldwide. Early detection helps in reducing the number of deaths. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. Historically, it was a difficult and time consuming process to review the medical images of breast cancer using ultrasound scan and identify the tumor in the breast . The objective of this case study is to use evaluate and classify the type of tumor using ultra sound breast images. After a detailed analysis and research, Ai labs developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky™ to automatically evaluate and classify the type of Breast tumor to aid in early treatment.

ULTRASOUND FETUS BRAIN

The evaluation of fetal brain can be critical because deficits in the perfusion (passage of blood flow) of this territory may lead to inadequate development of the central nervous system and even jeopardize fetal vitality. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. The objective of this case study is to evaluate the maturity of fetal ultrasound brain in a real maternal-fetal clinical environment to automatically classify fetal anatomical planes of Brain. After a detailed analysis and research, Ai labs developed and implemented a Proof of Concept (POC) using its proprietary engine Minsky™ to automatically evaluate the maturity of fetal brain via ultrasound images and classify the data image views accordingly.

WATER TREATMENT FORECAST

Global demand for water has been increasing as urban economic activity expands. A significant amount of effort is required to obtain clean water and the reduction of this effort requirement is a major concern for water utilities. The aim of this project was to predict if water is safe for human consumption based on the chemical composition (such as PH, Hardness, Total solids dissolved etc) for water produced or coming from different sources. This helped the client to make better decisions on whether or not to process the water for consumption.