Retail
Artificial Intelligence Predictive Analytics
Do you have a problem with inventory? Inventory management in the retail industry can be transformed by implementing predictive analytics technologies. Calculate demand predictions and sales to ensure efficient commodities allocation, purchasing, and restocking across a number of different locations and industries.
Analyze previous sales data and trends in order to better organise seasonal events in the coming season. Artificial intelligence in retail can be used for data analysis and visualisation in order to keep one step ahead of your retail competition.
Using NLP to Improve Your Competitive Advantage
Natural Language Processing can help you learn how your customers feel about your brand (NLP). Customer reviews can be collected and analysed using sentiment analysis technologies. Find out what’s holding you back from dominating the retail market, and how to fix it.
Segment your customers into distinct groups to better target your marketing efforts. To meet the demands of your customers, use data-driven insights. Increase your profitability by winning the hearts of your target audiences through the provision of customised experiences.
Utilize all of your retail data, both online and off, to derive relevant insights. Take a bird’s eye view of the entire business. Your POS, RFID, Inventory, or any other application may be simply integrated with Intellicus to give unified insights. By analysing customer behaviour across retail, e-commerce, and social channels, you can provide a truly omnichannel shopping experience to your customers. Transform POS operations, streamline the supply chain, increase staff productivity and morale, implement dynamic pricing and margin loss reductions using Intellicus sophisticated analytics. Improve consumer segmentation and profile, find market gaps, and discover new opportunities by forecasting demand and sales..
Aim to Boost Shop Performance
Utilize the power of advanced analytics to increase revenue and improve customer satisfaction in-store. Improve daily operations, sales tracking, inventory management, and customer and market trends by providing store managers with visual analytics. As a result of this information, they are able to better manage their employees’ time.
Location-Based Data for Merchandise
Heat mapping and analysis of SKU sales and inventory data can help improve in-store merchandising and optimise shelf space and product placement. Improve price and reduce losses by studying the market, competition, and other factors. A unified dashboard for all locations and their data can be created by using location analytics. Make data-driven decisions based on customer behaviour and sales data particular to a given place. Analytical methods can be used to determine where and how much demand there is for a product.
Promotions and Personalization in-store
Provide a tailored experience to boost client loyalty and engagement and increase income. Increase the effectiveness of marketing campaigns by delivering targeted messaging and discounts. Assemble a consumer-centric assortment mix and order products by size, predicting demand and providing a product and size-based mix. Automate the store so that it serves as a fulfilment centre for online orders as well as a sales point.
Healthcare
Insights from Healthcare Data That Empower You
In order to minimise costs, improve patient care and outcomes, and protect patient data, the Intellicus BI solution for healthcare gives you the insights you need. This and more, with complete data security, may be done for everything from anticipating patient demands to improving the patient-staff ratio to managing insurance claims.
Data Predictive Analytics & Healthcare Delivery Enhancement
Predictive analytics can help healthcare providers meet the requirements of individual patients and improve patient outcomes.
Big data and machine learning may make diagnostics simpler. Automate the detection of anomalies in patient clinical data with our machine learning-based predictive models..Analyze the results in order to adapt the intended treatment plan and navigate drug risks such as adverse reactions and prescription side effects. side. effects..
Improve patient outcomes by preventing chronic illnesses. With the help of patient-generated data, diseases such as diabetes and heart disease can be predicted. It is possible to predict the future outcomes of patients with high-risk conditions using predictive analytics technologies. Reduce the need for hospitalisation by developing individualised treatment plans and predictions.
OCR and Healthcare Business Processes Improvement
Let us handle the paperwork for you! With our OCR solutions, you can easily convert from paper to digital. Data capture, retrieval, and extraction can be used to improve healthcare business processes. All types of healthcare documents, such as patient records, medications, claims, reports, and invoices, can be easily digitised using OCR technology.
Streamline the exchange of health data between organisations by allowing for automated data entry. Use specialised OCR software in your hospital to automate time-consuming tasks and save money.
Create an AI pharma EHR that can predict and analyse clinical outcomes with ease. Medication demand can be forecasted and resources can be allocated efficiently. Pharmacists can use artificial intelligence to improve patient outcomes.
Analysis of Insurance Claims
Utilizing Intellicus powerful analytics, you can sift through enormous volumes of claims data, identify key performance indicators (KPIs), and develop strategies for the future. Claims losses can be reduced by keeping an eye out for any trends or anomalies in claims from all policies. To identify new policies, analyse policy and claim data. Determine how much the premium can be raised if any individual insurance is causing a larger number of claims. Ensure better healthcare services and policy improvements to reduce the amount of claims. Newer and better policies can be introduced to meet the needs of customers and benefit insurance businesses with improved client segmentation.
Analysis of Fraud and Risk
Machine learning can be used to evaluate data from patients, claims, and other sources to forecast future trends and identify risk ratings for patients. Search for links between patient care, financial performance, and policies in order to maximise all aspects of your business. Machine learning can be used to spot warning signs of fraud and to anticipate it before it happens. Monitor suspicious activity, evaluate the impact on various services that may be affected, and get warnings when suspicious activity occurs.
Reduce the Time and Money It Takes to Do Business
Hospital procedures can be viewed from a single location. Supply chain, financial, clinical operations and administration data should be integrated. In order to improve patient care and streamline processes while reducing waste, use this source of truth. The patient journey should be mapped and optimised based on the analysis of each stage and service utilised.
In order to reduce patient wait times, improve workforce planning, and maximise hospital resources, precisely forecast the demand for doctors and employees. Visual analytics can empower administration and make daily chores more efficient. Use analytics to enhance the patient experience, improve communication across clinical and non-clinical departments, and make data-driven choices across the company.
Aim to Better Serve Patients
Improve patient outcomes by providing value-based treatment based on advanced analytics. Access to the most critical KPIs and previous patient data can help healthcare practitioners make better decisions. Be on the lookout for process inefficiencies in order to improve patient outcomes and enhance the patient’s experience. Access to unified analytics can reduce the amount of time and money spent on re-inventing the wheel, resuV7 Data Labs ng in faster and more data-driven choices and a more efficient use of resources.
Diagnose patients who are at risk of readmission and conduct preventative measures. Compare the performance of physicians in terms of cost and quality to industry standards and identify areas for improvement. Doctors’ workloads can be reduced by increasing the number of patients they see. Coordinated care can be achieved by tracking KPIs across all departments, conducting cost analysis, and conducting KPI tracking.
Logistics
Manufacturing
Data from production units, PLCs, SCADA systems, supply chain operations as well as ERPs and CRMs may be gathered and analysed using Intellicus manufacturing analytics. data from manufacturing operations can be a game changer and enable data-driven strategic decisions if it’s properly analysed.
Observe the OEE
Advanced analytics can be used to identify and improve the manufacturing plant’s productivity. To keep tabs on OEE, compile and evaluate data from a variety of sources, including employees, machines, sensors, and Internet of Things (IoT) devices. Make sure that each machine, plant, and overall production setup is working at its maximum capacity and efficiency. Measure downtime, slowness, and other crucial KPIs. Maintaining a high level of availability, performance, and quality is essential to maximising productivity. By monitoring equipment and processes in real-time, floor supervisors will be able to identify the component that frequently fails and fix it before it causes production losses. It’s important to look at metrics like PPM and SPC as well as other metrics like downtime reasons as well as incidents, lost production, and so on.
Enhance Productivity
Analyze and monitor product quality in real time to reduce losses and improve customer satisfaction. Analyze and collect data from gauges and testing equipment in an automated manner. Maintain a close eye on crucial KPIs, like production yields and scrap percentages every order. Quality concerns and bottlenecks are identified, and benchmarks are established for future reference, as a result of this process. First pass yield, rework and reject costs, the amount of client returns, and more should all be taken into account. With real-time monitoring and threshold-based notifications, you may be alerted to process irregularities and take immediate action.
Estimated Consumption
Machine learning can be used to predict demand based on your past purchases and other forward-looking data. To avoid unpurchased inventory, limit risk, improve sales techniques, manage the production cycle, and increase prospects for growth, conduct a what-if study. Speculate on what might happen in the future and devise long-term plans.
Management of the supply chain.
Learn more about your supply chain by taking a 360-degree look at it. SCM, ERP, MES, logistics, and sales data can be used to identify existing supply chain concerns and red flags by connecting to internal and external data sources. Manage costs, quality, orders, and inventories more effectively by keeping up with customer trends. The best way to acquire the best deal is to compare the performance of vendors. Streamline the supply chain by coordinating demand and supply based on advanced forecasting.
Management of warehouses
In order to streamline your inventory, employ powerful analytics and dashboards to optimise your warehouses and warehouse management systems. Improve inventory organisation to shorten the time it takes to collect and transport products. Enhance the efficiency of product movement and the performance of warehouse workers. A business intelligence solution can help you find and eliminate overburdened employees and unnecessary expenditures. Measure stock on hand, turnover, age, mobility, and other variables. – Use a more efficient method of stocking shelves to reduce the amount of inventory that needs to be replenished.
Manufacturing is undergoing an analytics-driven transformation.
With Intellicus manufacturing analytics, you can make sense of massive amounts of production data gathered from a variety of sources. Optimize every step of the manufacturing process, from obtaining raw materials to selling the finished goods. Machine learning-driven advanced analytics can help you digitise, automate, and innovate in this Industry 4.0 transformation. With real-time analytics and data aggregation from your PLCs and SCADA systems as well as your supply chain operations as well as ERPs and CRMs, you can create a holistic view of your business and monitor critical indicators in real-time. Centralize monitoring and reduce costs; minimise risks; improve customer service; and increase coordination between supply chain, production, and sales departments.
E-Commerce
eCommerce and logistics are expanding at a time when nearly every industry is moving online. It has become increasingly necessary to build a strategy based on modern technology as the trust in eCommerce firms grows and competition increases. Using our data-driven approach and methodology, DataToBiz can help you beat the competition. When it comes to chatbots, virtual trial rooms, or any other technology, we can help.
Analysis of Customer Data Using Predictive Analytics
Your e-store isn’t bringing in the money it should be? E-commerce can benefit greatly from predictive analytics if it is properly implemented. Analyze real-time user behaviour, previous purchases, and products liked and rated in order to provide future recommendations for products…. AI solutions for E-commerce can help you increase sales by reducing the amount of pressure you put on your customers.
Predictive Analytics for Predicting Customer Churn
Are you sick and tired of seeing your consumers leave for competitors? Stop client turnover in E-commerce with the help of artificial intelligence (AI). Keep a close watch on client feedback, pricing, and competition in the marketplace. Before it’s too late, learn to recognise the early indicators of client attrition and the causes for it.
Using Predictive Analytics to Manage Inventory
What’s the trick to finding the right mix between overstock and understock? You may want to consider using predictive analytics models for inventory management. Staying well-stocked and saving money on storage is easier if seasonal trends are studied along with product demand and sales.
The Use of Predictive Analytics in the Study of Prices
E-commerce earnings can be maximised by using artificial intelligence. Real-time pricing analysis can be done with the use of custom predictive analytics tools. For pricing optimization, analyse historical product pricing, competitive pricing, customer behaviour, and activity.
Banking and Fintech
Industry challenges include challenging macroeconomic conditions, increased regulatory scrutiny, and new non-traditional competitors. In response to shifting market conditions, banks are moving from a product-centric to a customer-centric approach. Financial Services for BFS industry from V7 DATA LABS help you deliver outstanding client experiences and competitive business models while improving operational efficiency.
V7 DATA LABS ‘s “banking reimagine” approach, paired with advice and implementation services, has helped banks create innovative banking solutions that have benefited businesses. To generate business value, our reinvented banking services and supply architecture enables us to provide data-driven innovation in areas like as retail and commercial banking; payments; trade finance; capital markets; asset/wealth management; custody; and settlements.
V7 DATA LABS , as a digital banking solution provider, links you to your consumers via different digital channels. Innovative engagement methods, disruptive approaches, delivery excellence, a dependable thought partner ecosystem, and a world-class digital staff are just some of the ways V7 DATA LABS ‘s BFS Technology Solutions will add value to your firm.
Our unique Fintech solutions are designed to improve operational efficiency and customer service.
Data Prediction for Fraud Deterrence
Data anomalies in bank and credit card transactions, insurance claims and mortgage and loan applications can be detected in real time using Fintech predictive analytics. Financial IT systems can help prevent fraud and money laundering.
Credit Scoring Analytical Tools
Custom AI software can be used to flag particular businesses and clients and prevent loan debt. Analytical tools make it simple to assess a client’s credit history and identify credit default indications.. To make risk management and decision-making simpler, the financial technology industry should adopt artificial intelligence (AI).
Understanding Customer Retention Through the Use of Big Data
Looking for a plan that will keep your customers coming back for more? Try a data-driven approach. Financial IT solutions allow you to gain meaningful insights from your data and improve your business outcomes. With the help of predictive analytics, you can better understand how your customers utilise and appreciate the products and services you offer. For long-term growth and profitability, focus on your customers’ pain concerns.
Face Detection to Prevent Crime
Use computer vision in the financial sector. Face-recognition technology can be used to protect your business. Detecting unwanted access and keeping track of your personnel on the bank premises is made easier by recognising human faces. Using facial recognition, AI financial systems may restrict access to critical levels and rooms. A database of people who have been barred from the building can also be created. The security staff will be alerted as soon as surveillance systems recognise them.
Violent Behavior Detection Using Pose Estimation
Pose estimation techniques can unlock the potential of artificial intelligence in the financial sector. The surveillance system’s video can be used to recognise human actions and detect violent conduct. The use of artificial intelligence in finance can help reduce the risk of bank robbery.
Document Automation Using Data Capture and OCR
In order to protect confidential information, use ML-powered financial solutions. Data entry and capture solutions that are reliable will help you avoid errors, misuse, and loss of data.
With enhanced invoice data collection, you can streamline your work procedures. Data may be retrieved from massive amounts of information in a matter of seconds. Reduce the time it takes to process invoices and increase productivity. Automate repetitive activities and reduce labour costs by integrating Fintech OCR software into your daily operations.
NLP for Customer Service & Market Research
NLP can be used in Fintech to empower decision-making. Observe customer input on social media, surveys, and customer feedback forms. Use sentiment analysis to gain insights into your customers’ wants and pain points, and come up with personalised offers. Adjust client acquisition, experience and retention strategies based on data.
Do you want to outdo your banking business rivals? Social media data should be merged to gain a better understanding of the current trends and customer preferences in the market.
Telecommunication
The Communications Services Providers (CSPs) of today and tomorrow are important to the future of the telecom business in today’s digital world. To do this, a communications system that is more adaptable and has lower operating costs than the proprietary-centric networks of the past must be implemented.
In order to accomplish this goal, V7 Data Labs is collaborating with the leading CSPs, bringing capabilities such as artificial intelligence (AI) and hybrid cloud for flexibility and innovation, industry experience, as well as a global delivery presence, to the table.
The telecommunications business is the only one that generates infinite amounts of data. Data management methods that have been in use for decades can quickly lead to extinction. Our mission is to push you to the next level of growth so that you may outperform your competition. This includes data gathering, management, analytics, and automation, among other things.