Platform
Decision.Intelligence.Communication.Engine.
D.I.C.E.
D.I.C.E.
Data Model
The D.I.C.E. data model is made up of five components that allows complex decision processes to be represented
Entities
Flexible data model to represent any use case.
Relationships
Linking entities model the data hierarchy.
Capabilities
Workflows controlling creation, transformation, interactions, and destruction of entities.
Display
Dashboards and reports to allow humans to explore the data and action any recommendations
APIs
Connections into and out of the system, data to be collected, and decisions to be made.
FILES
DATABASES
AUDIO
APIS
Data Entities
Data Entities
Data Entities
Data Entities
ML
Microservice
ML
Microservice
ML
Microservice
FILES
DATABASES
AUDIO
APIS
Recommendation
D.I.C.E.
Decision Pipeline
D.I.C.E.
Platform
The D.I.C.E. Platform from Personar assists organizations in effectively utilizing their abundant data. It streamlines the process of analyzing and processing large, complex datasets, distilling them into key actionable insights. D.I.C.E. can either augment the expertise of existing professionals by providing them with targeted information and AI-generated recommendations, or it can autonomously execute decisions based on its recommendations. This allows organizations to make more informed and efficient decisions by leveraging advanced AI capabilities.
DECISION
Organisations have a wealth of data at their fingertips. But this data is of no use unless it can be leveraged to make better decisions. By leveraging the D.I.C.E. platform, an organisation can streamline the analysis and processing of large, complex datasets and boil it all down to the key actions. D.I.C.E. can play a supporting role to existing subject matter experts by presenting them the specific information needed along with an AI-powered recommendation, or D.I.C.E. can act on its recommendations and automatically make decisions.
INTELLIGENCE
D.I.C.E. machine learning microservices bring the power of modern AI to the platform in a streamlined, optimised and auditable way. Different types of machine learning can be leveraged in a seamless data pipeline, allowing for identification, transformation and understanding of the underlying data. Rather than one generalised, massive AI model, D.I.C.E. employes specific models for specific purposes. These models can be trained, refined and updated independently, giving an organisation full control over what's going on inside.
Computers and people see information in very different ways. By seamlessly translating between those two worlds, the D.I.C.E. platform can work with almost any type of data and prepare that data for whatever is next. D.I.C.E. can pulling in information from databases, emails, documents or even audio steams, and transform it into something a computer can understand. Once the data analysis is done and the decisions are ready, D.I.C.E. can present that information to a human as a summary or a dashboard or recommendation, or pass that information to another computer system in whatever format is needed
COMMUNICATIONS
The flexible and dynamic nature of the D.I.C.E. platform allows it to quickly be deployed to power a wide variety of use cases. All of the data models, workflows and ML capabilities can be quickly configured to meet almost any requirements, and can be adjusted quickly and easily as those requirements evolve.
ENGINE
