SALES FORECASTING

The objective of this project was to predict the weekly sales for a Retail corporation by store type, store location based on past data and future economic parameters like CPI, fuel price, unemployment. This helped the client to improve cash flow and manage the Supplydemand for the products sold. The future economic forecast data is collected from external sites and databases using Robotic Process Automation (RPA).

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.

EMPLOYEE RETENTION

Typically, employee attrition is a major challenge for companies worldwide. The objective of this project was to predict employee attrition for a Multinational software-based company on parameters like Supervisor, wages, distance from home, tenure with company, travelling, overtime etc. This helped the client to make better decisions to curtail employee attrition rate. Current employee related data is collected from company’s internal databases / HR systems using Robotic Process Automation (RPA).

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.

RPA FOR ERP BASED PAYROLL PROCESSING

The Client is a large innovative, knowledge-based energy and utility enterprise serving the Power, Water and Environmental sectors and provides IT solutions for Energy/Hydro industry. With offices in multiple countries, the HR Department handles various processes such as talent acquisition payroll processing etc. Each of these processes comprise of several activities that are repetitive and time consuming but critical for employee satisfaction.

RPA FOR APPLICATION SUPPORT

The Client is a large Power Distribution Company based in Europe where we provide 24/7 Software Maintenance Support from our remote engineering centers. We provide support for several applications such as SAP, MS Azure, Oracle, Primavera, eWay, IBM Integration Bus (IIB), Microsoft Business Intelligence, Websphere, Weblogic, Alfresco, etc. by Class of Service required (platinum, Gold 24X7, Gold 12X5, Silver, Bronze). Incident management is handled by ServiceNow (SNOW).

RPA FOR ERP BASED HR ACTIVITIES

The Client is a large innovative, knowledge-based energy and utility enterprise serving the Power, Water and Environmental sectors and provides IT solutions for Energy/Hydro industry. With offices in multiple countries, the HR Department handles various activities such as on-boarding, termination, off-boarding etc. Each of these processes comprise of several activities that are repetitive and time consuming but critical for employee satisfaction.

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.

ENERGY FORECAST

Allocation of power (to meet real time demand) between traditional power and alternate power has become a challenge worldwide. The aim of this project was to predict how much power is available from alternative energy based on geo location, temperature etc. This helped the client to make better decisions on utilization of other sources of energy. The forecast weather data was collected from external sites using Robotic Process Automation (RPA) and used by the Minsky™ generated models to predict realtime solar power generation.

INSURANCE CLAIMS PROCESSING

This case study is based on data from a large global insurance company which is engaged in providing Auto 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 repetitive and time consuming but critical for employee satisfaction. To overcome this, we developed and implemented RPA (Robotic Process Automation) for monitoring the incoming customer claims received via emails in the form of PDF. Our solution captures the required data from each claim which is then populated in the Master excel sheet and emailed to the company’s head of claims. In addition, the 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 a high risk/low risk prediction for each claim that are emailed out to 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.

MORTGAGE LOAN APPLICATION PROCESSING

Globally, the mortgage approval process is time consuming and also fraud has become a major ongoing concern for all bankers/ lenders. The aim of this project was to automate the loan process steps and also categorize each application based on Risk Level Predictions using our Proprietary AI Engine. This allows the loan processors to process the applications according to the risk levels. The process of verification of key data like (age, address, income) against the submitted documents is also handled by RPA. This helped the client to reduce the loan processing times/cost and also minimize high risk loans.

CHARITABLE ORGANIZATIONS

As society evolves and changes over time, new problems and crises also arise. Fortunately, these new issues can also give rise to innovation, new solutions to help nonprofit organizations. Imagine trying to solicit donations for your organization. You’ve got a list of people to communicate with, but you don’t know anything about them aside from their names. You don’t even know that they’re moderately interested in your cause. Nonetheless, you decide to cast out your net which is not really a very effective fundraising strategy. Unfortunately, that’s precisely what every social good organization without a defined nonprofit target audience is doing. There are nearly 8 billion people on earth, and trying to appeal to all of them is impossible. As such, you’ve to locate and define your target audience: the people who want to support you. When you do this, it’s much easier to target the people who are likely to support your cause and make the most of your fundraising efforts.

RPA FOR ERP BASED HR RECRUITMENT ACTIVITIES

The Client is a large innovative, knowledge-based energy and utility enterprise serving the Power, Water and Environmental sectors and provides IT solutions for Energy/Hydro industry. With offices in multiple countries, the HR Department handles various activities such as onboarding, termination, off-boarding etc. Each of these processes comprise of several activities that are repetitive and time consuming but critical for employee satisfaction. To overcome this, we developed and implemented RPA (Robotic Process Automation) for the entire Recruitment process that starts with monitoring the incoming job applications and the resume. Then OCR is performed on PDF or word formatted resume and categorize them by skills and job postings. An excel sheet is then generated by the bot and sent to the HR Dept. daily. Based on HR feedback received by the bot from an email, interview links are shared with the appropriate candidate(s). Then, the bot monitors emails from HR for final selection of candidates and offer letters are automatically emailed out to all the selected candidates with appropriate forms/attachments based. Solution was integrated with an existing HR and Finance system and went live in 12 weeks.

DATA MIGRATION USING RPA

Typically data validation, migration and entries are the process of making sure that the data has been checked for errors and entered correctly in the document. But when it comes to huge volume of data with business organizations, manual data validation, migration and entries becomes quite tedious and error prone. Every bit of data is critical from an accuracy standpoint and even a small error can put the businesses at great risk. As a result of the manual approach if applied in the long term can hamper an organization’s interoperability initiatives and hurts the data’s integrity.

RPA IMPLEMENTATION FOR PROJECT MANAGEMENT SOFTWARE

Typically, our client/customer has multiple contracts/projects/tasks to find suitable vendors in a short time for a particular project. The time involved in doing the whole process manually is long and tedious and finally may not yield the desired results due to improper vendor selection. For this process, dedicated resources are allocated to execute this process which takes a significant effort to complete the entire process which increases cost to company and the time period.