USE CASES

  • All
  • FINANCE & INSURANCE
  • MANUFACTURING
  • PHARMA & BIOTECH
  • PUBLIC
  • RETAIL & MARKETING
  • TRANSPORT & LOGISTICS
  • UTILITIES
 
EMAIL ROUTING – CLASSIFICATION
EMAIL ROUTING – CLASSIFICATION
MESSAGE CATEGORIZATION
MESSAGE CATEGORIZATION
EMAIL ROUTING – CLASSIFICATION IN THE PUBLIC SECTOR
EMAIL ROUTING – CLASSIFICATION IN THE PUBLIC SECTOR
PREDICTION OF ENERGY EFFICIENCY
PREDICTION OF ENERGY EFFICIENCY
CLIENT REACTION BASED ON SCENARIOS – FINANCE
CLIENT REACTION BASED ON SCENARIOS – FINANCE
PRODUCTION PLANNING
PRODUCTION PLANNING
SORTING AND SCRAP REDUCTION – PHARMA
SORTING AND SCRAP REDUCTION – PHARMA
PREDICTION OF SERVICE CASES – MANUFACTURING
PREDICTION OF SERVICE CASES – MANUFACTURING
INVENTORY PREDICTION – TRANSPORT
INVENTORY PREDICTION – TRANSPORT
CONTENT COMPARISON – PUBLIC
CONTENT COMPARISON – PUBLIC
IN-PROCESS CONTROLS – ERRORS IN MANUFACTURING
IN-PROCESS CONTROLS – ERRORS IN MANUFACTURING
PAYBACK OF ACCOUNT PAYABLE
PAYBACK OF ACCOUNT PAYABLE
DOCUMENT SEARCH – PHARMA
DOCUMENT SEARCH – PHARMA
PREDICTION OF SERVICE CASES
PREDICTION OF SERVICE CASES
ENVIRONMENT MONITORING
ENVIRONMENT MONITORING
PREDICTIVE MAINTENANCE – MANUFACTURING
PREDICTIVE MAINTENANCE – MANUFACTURING
INVENTORY PREDICTION – PHARMA
INVENTORY PREDICTION – PHARMA
PRICE PREDICTION
PRICE PREDICTION
MARKET DATA CLEANING
MARKET DATA CLEANING
CHATBOT – PUBLIC
CHATBOT – PUBLIC
CREDIT SCORING
CREDIT SCORING
IN-PROCESS CONTROLS – ERRORS IN PHARMA
IN-PROCESS CONTROLS – ERRORS IN PHARMA
CATEGORIZE COMPANIES OR INDIVIDUALS
CATEGORIZE COMPANIES OR INDIVIDUALS
PHRASE DETECTION
PHRASE DETECTION
CHURN PREDICTION – INSIGHTS AND LIKELIHOOD OF CHURN
CHURN PREDICTION – INSIGHTS AND LIKELIHOOD OF CHURN
PREDICT TIME ON A SERVICE REQUEST
PREDICT TIME ON A SERVICE REQUEST
PRODUCTION PLANNING
PRODUCTION PLANNING
CASE COMPLEXITY
CASE COMPLEXITY
TIME TO DELIVERY PREDICTION
TIME TO DELIVERY PREDICTION
WAREHOUSE ASSIGNMENT
WAREHOUSE ASSIGNMENT
CLIENT REACTION BASED ON SCENARIOS – PUBLIC
CLIENT REACTION BASED ON SCENARIOS – PUBLIC
INVENTORY PREDICTION – TIMING OF PURCHASES
INVENTORY PREDICTION – TIMING OF PURCHASES
CHURN PREDICTION – LIFECYCLES AND LIKELIHOOD OF CHURN
CHURN PREDICTION – LIFECYCLES AND LIKELIHOOD OF CHURN
PREDICTIVE MAINTENANCE – PHARMA
PREDICTIVE MAINTENANCE – PHARMA
RECOMMENDER SYSTEM
RECOMMENDER SYSTEM
CHURN
CHURN
CUSTOMER TARGETING
CUSTOMER TARGETING
LEAD QUALIFICATION – LOWERING ACQUISITIONS COST
LEAD QUALIFICATION – LOWERING ACQUISITIONS COST
SETTLEMENT PREDICTION
SETTLEMENT PREDICTION
DEMAND FORECASTING FOR ENERGY
DEMAND FORECASTING FOR ENERGY
PREDICTION OF SERVICE CASES – UTILITIES
PREDICTION OF SERVICE CASES – UTILITIES
INCREASE OUTPUT – PERFECT BATCH
INCREASE OUTPUT – PERFECT BATCH
DOCUMENT SEARCH – MANUFACTURING
DOCUMENT SEARCH – MANUFACTURING
CHURN PREDICTION – PROACTIVE MEASURES
CHURN PREDICTION – PROACTIVE MEASURES
SLOTTING OF GOODS
SLOTTING OF GOODS
EMAIL ROUTING – REDUCING MANUAL WORK
EMAIL ROUTING – REDUCING MANUAL WORK
INVENTORY PREDICTION – MANUFACTURING
INVENTORY PREDICTION – MANUFACTURING
PREDICTIVE MAINTENANCE – UTILITIES
PREDICTIVE MAINTENANCE – UTILITIES
CHATBOTS – UTILITIES
CHATBOTS – UTILITIES
INCREASE OUTPUT – MODELLING PATTERNS
INCREASE OUTPUT – MODELLING PATTERNS
FRAUD PREDICTION
FRAUD PREDICTION
PAYMENT MATCHING
PAYMENT MATCHING
DEMAND FORECASTING – INVENTORY
DEMAND FORECASTING – INVENTORY
LEAD QUALIFICATION – UP TP 80 % ACCURACY
LEAD QUALIFICATION – UP TP 80 % ACCURACY
CLIENT REACTION BASED ON SCENARIOS – TRANSPORT
CLIENT REACTION BASED ON SCENARIOS – TRANSPORT
SORTING AND SCRAP REDUCTION – MANUFACTURING
SORTING AND SCRAP REDUCTION – MANUFACTURING
 
  • All
  • FINANCE & INSURANCE
  • MANUFACTURING
  • PHARMA & BIOTECH
  • PUBLIC
  • RETAIL & MARKETING
  • TRANSPORT & LOGISTICS
  • UTILITIES
 
PRODUCTION PLANNING
PRODUCTION PLANNING
A model can identify hidden patterns in historical sales data - such as those in seasonal demand and subsidiary behavior or new product launches
CATEGORIZE COMPANIES OR INDIVIDUALS
CATEGORIZE COMPANIES OR INDIVIDUALS
A non-supervised learning algorithm clusters individuals or companies based on descriptive variables
EMAIL ROUTING – REDUCING MANUAL WORK
EMAIL ROUTING – REDUCING MANUAL WORK
Emails get classified by using a supervised learning algorithm, up to 40% reduction in manual work at support desk
CLIENT REACTION BASED ON SCENARIOS – FINANCE
CLIENT REACTION BASED ON SCENARIOS – FINANCE
A supervised model that predicts which client might react in a different market scenario. Later this model can be used to predict which clients react in a simulated market scenario
MESSAGE CATEGORIZATION
MESSAGE CATEGORIZATION
Classification of messages, emails or documents for human or automated processing
CONTENT COMPARISON – PUBLIC
CONTENT COMPARISON – PUBLIC
An algorithm compares the content of documents and highlights similarities and differences
CHURN PREDICTION – LIFECYCLES AND LIKELIHOOD OF CHURN
CHURN PREDICTION – LIFECYCLES AND LIKELIHOOD OF CHURN
Creation of a model that analyzes past client lifecycles and likelihood of churn. By using state of the art shapely additive explanation value analysis, explaining what actions to take to reduce the churn probability
INCREASE OUTPUT – PERFECT BATCH
INCREASE OUTPUT – PERFECT BATCH
Modelling patterns between input and output of the batches as well as performance parameters analysis can increase output substantially
DEMAND FORECASTING – INVENTORY
DEMAND FORECASTING – INVENTORY
Anticipating future demand is important as inventory needs to be bought several weeks or months in advance. Accurate forecasts can prevent from losing revenue due to empty stocks
PREDICTIVE MAINTENANCE – MANUFACTURING
PREDICTIVE MAINTENANCE – MANUFACTURING
Malfunctions or poor maintenance can result in expensive downtime. An algorithm predicts the risk of equipment failure in production
DOCUMENT SEARCH – MANUFACTURING
DOCUMENT SEARCH – MANUFACTURING
Searching and classifying quality documents can save time and help identify areas for improvement
PRICE PREDICTION
PRICE PREDICTION
Determining the best price for a product by performing market analysis and product comparison will keep the company competitive and attractive for the customers
SLOTTING OF GOODS
SLOTTING OF GOODS
An unsupervised learning algorithm used to show relationships between goods and which goods are typically ordered together - reducing the picking time
PAYMENT MATCHING
PAYMENT MATCHING
Automating matching of incoming and outgoing payments - and presenting the processor with intelligent choices for “best fit” matches
PAYBACK OF ACCOUNT PAYABLE
PAYBACK OF ACCOUNT PAYABLE
For this case a supervised learning approach is used to predict from new customers whether they will be able to pay their accounts payable on time
CHURN
CHURN
Creation of a model that analyzes past client lifecycles and the likelihood of churn. Applying state of the art Shapley additive explanation value analysis to explain what actions are to be taken to reduce the churn probability
FRAUD PREDICTION
FRAUD PREDICTION
Predict and find fraud patterns that cannot be seen using traditional rule-based methods
DEMAND FORECASTING FOR ENERGY
DEMAND FORECASTING FOR ENERGY
Prediction demands with a supervised learning algorithm, predict the demand for energy and manage its production
CLIENT REACTION BASED ON SCENARIOS – PUBLIC
CLIENT REACTION BASED ON SCENARIOS – PUBLIC
A model predicting which client might react in a specific scenario
INCREASE OUTPUT – MODELLING PATTERNS
INCREASE OUTPUT – MODELLING PATTERNS
Modelling patterns between input and output of the batches and analyzing performance parameters can increase output substantially
CASE COMPLEXITY
CASE COMPLEXITY
Prediction of difficult cases that might take longer to process
PREDICTIVE MAINTENANCE – UTILITIES
PREDICTIVE MAINTENANCE – UTILITIES
Malfunctions or poor maintenance can result in expensive downtime. An algorithm predicts the risk of equipment failure and need for maintenance
CHURN PREDICTION – INSIGHTS AND LIKELIHOOD OF CHURN
CHURN PREDICTION – INSIGHTS AND LIKELIHOOD OF CHURN
A supervised learning algorithm predicting whether a customer is most likely to leave a service or company as a customer, together with insights into reasons for churn
SORTING AND SCRAP REDUCTION – PHARMA
SORTING AND SCRAP REDUCTION – PHARMA
Scrap of good products must be minimized and scrap of poor products must be hundred percent. This often results in over scrapping of products
PREDICTIVE MAINTENANCE – PHARMA
PREDICTIVE MAINTENANCE – PHARMA
Malfunctions or poor maintenance can result in expensive downtime. An algorithm predicts the risk of equipment failure and need for maintenance
INVENTORY PREDICTION – TIMING OF PURCHASES
INVENTORY PREDICTION – TIMING OF PURCHASES
Inventory depletion due to customer demand should be balanced by the purchase of new inventory. AI technology can help adjust the timing of purchases right to maintain inventory availability while minimizing ordering and shipping costs
EMAIL ROUTING – CLASSIFICATION IN THE PUBLIC SECTOR
EMAIL ROUTING – CLASSIFICATION IN THE PUBLIC SECTOR
Emails get classified by using a supervised learning algorithm, reducing manual work
PREDICTION OF SERVICE CASES – UTILITIES
PREDICTION OF SERVICE CASES – UTILITIES
A supervised algorithm predicts service cases, increasing accuracy in planning of service and maintenance
LEAD QUALIFICATION – LOWERING ACQUISITIONS COST
LEAD QUALIFICATION – LOWERING ACQUISITIONS COST
Focus on acquiring the right customers is paramount to ensure low acquisition cost and high customer lifetime. An algorithm can help sort out which leads are worth spending time and efforts on
PRODUCTION PLANNING
PRODUCTION PLANNING
A model can identify hidden patterns in historical sales data, such as those in seasonal demand and subsidiary behavior or new product launches
ENVIRONMENT MONITORING
ENVIRONMENT MONITORING
Incubation time for environmental samples counts in days and weeks with the risk of production being non-compliant
SETTLEMENT PREDICTION
SETTLEMENT PREDICTION
Predicting whether a settlement will be effectuated before a given deadline or not, based on actual and historical settlements
DOCUMENT SEARCH – PHARMA
DOCUMENT SEARCH – PHARMA
Searching and classifying quality documents can save time and help identify areas for improvement
PHRASE DETECTION
PHRASE DETECTION
An algorithm scanning contracts and detecting phrases that are not allowed to use
INVENTORY PREDICTION – TRANSPORT
INVENTORY PREDICTION – TRANSPORT
The sale of goods gets predicted and with this the algorithm gives recommendation for store inventory management
PREDICTION OF SERVICE CASES
PREDICTION OF SERVICE CASES
A supervised algorithm predicting service cases, and thus increasing accuracy in the planning of service and maintenance
CREDIT SCORING
CREDIT SCORING
Using machine learning algorithms to take actual historical data to determine creditworthiness and repayment ability
CHATBOT – PUBLIC
CHATBOT – PUBLIC
A more dynamic Q&A page improving instant communication and interaction with clients
EMAIL ROUTING – CLASSIFICATION
EMAIL ROUTING – CLASSIFICATION
Emails get classified by using a supervised learning algorithm, reducing manual work
RECOMMENDER SYSTEM
RECOMMENDER SYSTEM
Recommendation engines are a very powerful tool to provide a personalized shopping experience for the customers by tailoring products based on their browsing history
CHURN PREDICTION – PROACTIVE MEASURES
CHURN PREDICTION – PROACTIVE MEASURES
An algorithm defining which customers are going to leave and for what reasons, thus empowering marketing team to take proactive measures
IN-PROCESS CONTROLS – ERRORS IN MANUFACTURING
IN-PROCESS CONTROLS – ERRORS IN MANUFACTURING
Many product errors or machine malfunctions are spotted late in the manufacturing process due to manual in-process controls
CHATBOTS – UTILITIES
CHATBOTS – UTILITIES
Improving instant communication with clients and having a more dynamic Q&A page that customers like to use
LEAD QUALIFICATION – UP TP 80 % ACCURACY
LEAD QUALIFICATION – UP TP 80 % ACCURACY
A supervised learning algorithm predicts whether a customer is most likely to become a lead. ~80 % accurate prediction of chance to convert a lead
TIME TO DELIVERY PREDICTION
TIME TO DELIVERY PREDICTION
A supervised learning algorithm predicts whether goods might be delivered on time or not
CUSTOMER TARGETING
CUSTOMER TARGETING
Running marketing campaigns for carefully selected customers based on the key attributes can be automated, boosting ROI while minimizing marketing spends
INVENTORY PREDICTION – MANUFACTURING
INVENTORY PREDICTION – MANUFACTURING
The sale of goods gets predicted and based on that algorithm gives recommendations for store inventory management, allowing inventory or trash reduction
CLIENT REACTION BASED ON SCENARIOS – TRANSPORT
CLIENT REACTION BASED ON SCENARIOS – TRANSPORT
A model predicting which client might react in a specific scenario
INVENTORY PREDICTION – PHARMA
INVENTORY PREDICTION – PHARMA
The sale of goods gets predicted and based on that algorithm gives recommendations for store inventory management, this allows reducing of inventory of trash
PREDICT TIME ON A SERVICE REQUEST
PREDICT TIME ON A SERVICE REQUEST
A supervised learning algorithm predicting how long a request might take to be solved: reducing questions on how long it will take
PREDICTION OF SERVICE CASES – MANUFACTURING
PREDICTION OF SERVICE CASES – MANUFACTURING
A supervised algorithm predicts service cases, increasing accuracy in planning of service and maintenance
PREDICTION OF ENERGY EFFICIENCY
PREDICTION OF ENERGY EFFICIENCY
An algorithm labels homes with energy efficiency class. Decreases the manual work that needs to be done when assigning energy efficiency classes to homes. Can also be applied as a prescan option
WAREHOUSE ASSIGNMENT
WAREHOUSE ASSIGNMENT
An algorithm processing shipment requests and assigning them to a warehouse based on its location and how the inventory fits the clients' needs
IN-PROCESS CONTROLS – ERRORS IN PHARMA
IN-PROCESS CONTROLS – ERRORS IN PHARMA
Many product errors or machine malfunctions are caught late in the manufacturing process, due to manual in-process controls
SORTING AND SCRAP REDUCTION – MANUFACTURING
SORTING AND SCRAP REDUCTION – MANUFACTURING
Scrap of good products should be minimized and scrap of poor products should be close to hundred percent. It often results in over scrapping of products
MARKET DATA CLEANING
MARKET DATA CLEANING
Detecting anomalies (e.g. missing values) and then assigning abnormal values an averaged/fitting value
 

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