Together with our fully comprehensive Cloud Pak for Data test and demo platform, we can demonstrate the functionality of the platform in interaction with the accelerators to interested customers. Initially we do so with the demo data available for the use case, after consultation we can adapt the use case for our customers in close cooperation with them, import their data and thus make them experience the real added value of the faster project entry through the combination of "IBM AI Platform" and accelerators.
In many projects with a strong technical focus, companies often start from scratch: Requirements are developed completely from zero, and during implementation, attempts are made to implement them as precisely as possible. This can already influence the willingness to start projects and the implementation thus becomes not only individual, but also extensive. In AI or Data Science projects, it is no different and often this approach becomes an entry hurdle.
For a quick start in certain use cases, specifically for certain business areas or industries, IBM offers so-called accelerators based on the "Cloud Pak for Data" solution, which serve as a template for project development and can thus significantly accelerate the implementation of these use cases. The platform itself provides all the necessary functions for all types of analytics projects, and the accelerators provide the respective content.Get in touch
IBM accelerators for these business areas and industries
There are more than 40 use cases available. On request, we can provide any accelerator in our platform:
Staff Optimization: Manpower management with mathematical optimization Contact Center Insights: Insights using AI on structured and unstructured data.
Energy suppliers and service providers:
Energy Demand Planning: Support of planning with mathematical optimization Payment Risk Predicition: Using Data Science to identify potentially defaulting customers Attrition Prediction: Identify candidates for customer programs using Data Science
Claims Leakage: Optimization of damage payments Loss Estimation: Use of (satellite) imagery for AI-supported damage assessment after natural disasters Reduce Weather Risks: Use of weather data for early detection of severe weather events.
Get to know the individual accelerators and their use cases:
- Determination of required staff was often delegated to local managers in the past
- Reduction of possible overhangs through adjusted staff planning
- Staff must still deliver good service to the customer
- Optimizing staffing levels by determining the best distribution of staff per area/location/machine, etc.
Contact Center Insights:
- Customer questions and complaints reach the company through diverse, non-connected channels
- Customer inquiries and complaints about services and products are delivered in a variety of ways and formats, including text and voice
- Manual understanding of content, relationships, and patterns is cumbersome, slow, and expensive
- AI-powered understanding of customer inquiries across boundaries of channel, format, and time
Energy Demand Planning
- Producing too much energy wastes valuable resources; too little can cause blackouts
- In particular, accurately predicting renewable energy yields is problematic
- Combining traditionally separate processes for forecasting, optimization, and planning into a single, integrated solution
- Predefined, proven algorithms with very good forecast accuracy
Payment Risk Prediction
- Late or missed payments impact the financial health of the organization
- Understanding the context of missed payments can help avoid them
- Professional customers expect 360° view of the customer
- Identification of customers, with the ability to take timely action
- In deregulated markets, new players have a hard time identifying the right customers willing to switch
- Acquiring a new customer vs. retaining an existing customer is about six times more expensive
- Identify customers willing to switch
- Improve understanding of AI model to increase accuracy
- Unclaimed damage sums are a problem in the insurance industry
- Inefficient processes cost insurance companies $30 billion worldwide
- Reducing leakage can typically reduce claim costs by 5-10%.
- Context in claim data can provide clues as to which claims are potentially not being handled optimally
- Increasing amount of large claims
- Difficulty in estimating losses and thus the loss amount
- AI-supported analysis of satellite images (before-after)
- Automatic detection of damage
- Automatic calculation of damage amount based on assumptions
Reduce Weather Risks
- After major losses, e.g. natural disasters, a lot of data is available in different forms and formats that have to be used for analysis
- Platform for analysis, visualization and prediction of a wide variety of data in any quantity and structure
We are here for you.
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We would be happy to advise you in a non-binding meeting and show you the potential and possible uses of IBM Cloud Pak for Accelerators for your company. Simply leave your contact details and we will get back to you as soon as possible.