Quality beats quantity.
Solutions: the heart of good service. solvatio® X solutions are based on AI in the form of machine learning. Next Best Actions (NBA) are the result of in-depth automated data inspection and analysis and we use this data for the continual improvement of our solutions.
solvatio® X is therefore a learning system, making use of internal and external data, mixing it with crowd sourced information from day-to-day operations as well as from agent activity in order to create suitable follow-up actions. This creates hybrid intelligence, based on analysed data and agent actions, that guarantees maximum quality while minimising required input.
solvatio® X machine learning saves time for inhouse agents and customers and reduces overall time spend on technical support.
My name is Forest. Random Forest.
For solution classification, solvatio® X uses Random Forest. In addition to fast training based on enormous data volumes from historic cases, Random Forest especially enables fast data evaluation based on parallel processing. It also supports regression and thereby allows the modulation of interdependencies for seemingly non-interdependent variables.
In such a complex environment, involving the diagnosis of technical systems and environments with a variety of diverse components, this capacity of Random Forest makes it a valuable AI partner in solvatio ® X.
With proven time savings of over 36% per call, achieved by offering the most valuable solution, NBA becomes an indispensable partner for your agents.
MACHINE LEARNING (NBA)
Open to the world.
Next to Random Forest algorithm, solvatio® X is also equipped with a machine learning API that enables any external AI processes and services to be integrated into solvatio® X’s diagnostic and solution-finding process and then to be used alone or in conjunction with another.
In this way, solvatio® X is not just able to work with internal data but also enables the involvement of external Big Data Lakes and their ML outcomes. It therefore also enables independent solution evaluation based on existing data.
The ML MAPPER available in solvatio® X STUDIO provides a simple solution for mapping externally derived outcomes onto corresponding automation processes. It guarantees a short time to market and reduced workload when dealing with ML in solvatio® X.
Next Best Value.
Machine Learning in the form of NBA adds value on several levels. Instead of designing and implementing rather static processes and forcing them onto customers and inhouse agents, ML enables a results-oriented service process while keeping the reported problem in constant focus.
The inhouse agent wastes less time following rigid processes but gets immediate access to dynamic solutions. A BOT dialogue does not depend on lineary dialogue processing but reacts dynamically to the user’s data and statements. In SELF SERVICE dynamic solutions can be executed automatically instead of having to send process-driven data requests into a triage system.
NBA means less time spent on static processes and offer maximum return on time invested, with complete quality control guaranteed via the second opinion mode. It also enables free dynamic decision-making for inhouse agents and users.