diwo maximizes the value of AI investments by deeply understanding your business, applying context and constantly recommending strategies for growth.

diwo maximizes the value of AI investments by deeply understanding your business, applying context and constantly recommending strategies for growth.

 
 
 

Smarter Decisions.

diwo transforms decision-making by continually sensing potential business risks and opportunities, explaining the potential impact and recommending interactive strategies to address them. Users can model various scenarios before choosing one that most optimally balances between competing priorities.

Guided Conversations.

Users converse with diwo through a simple, natural language interface. Unlike tools that offer a simple Q&A dialog, diwo continually senses users’ context and guides them towards deeper insights and more relevant analyses to speed up their problem solving.

Continuous Observations.

diwo’s continuous observations and streaming analytics support operational decision-making. Interactive visuals not only offer users a bird’s-eye view of their business, but also allow users to understand the impact of their decisions in real time.
 
 
 

Smarter Decisions.

diwo transforms decision-making by continually sensing potential business risks and opportunities, explaining the potential impact and recommending interactive strategies to address them. Users can model various scenarios before choosing one that most optimally balances competing priorities.

Guided Conversations.

Users converse with diwo through a simple, natural language interface. Unlike tools that offer a simple Q&A dialog, diwo continually senses users’ context and guides them towards deeper insights and more relevant analyses to speed up their problem solving.

Continuous Observations.

An interactive experience not only offers users a bird’s-eye view of their business, but also allows users to understand the impact of their decisions in real time.

diwo’s patented technology leverages a business semantic graph to understand user context, correlate insights from multiple models, and identify the most relevant and impactful business opportunities automatically.

 
 
 
 
 
 
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“Data Sources:
diwo natively consumes data from multiple sources without time-consuming and costly migrations. The operational data source systems then feed the knowledge object store, data and ML pipelines and compute engine.”

“Semantic Graph:
The rich semantic layer allows diwo to capture the complete business context by embedding business and data definitions, correlations among them, KPIs and best practices.”

“In-Memory Computing:
Compute engine which continually senses trends in incoming data to uncover new opportunities and explores correlations among the outputs of AI/ML, optimization and simulation models to produce the most informed recommendations.”

“Knowledge Object Store:
Comprehensive database that includes detailed data from all designated operational sources, synthesized within diwo, and provides a complete baseline for observations and recommendations.”

“Data and ML Pipelines:
Deep learning algorithms that ensure continuous learning and observations that empower users to identify immediate risks and opportunities for growth.”

“GUI to User Interface:
A simple, natural language interface presents results and recommendations in the user’s context, masking the underlying complexity and making it easy for decision makers to understand, interact and act.”

diwo’s patented technology leverages a business semantic graph to understand user context, correlate insights from multiple models, and identify the most relevant and impactful business opportunities automatically.

 
 
 
 
 
 
1
1

“Data Sources:
diwo natively consumes data from multiple sources without time-consuming and costly migrations. The operational data source systems then feed the knowledge object store, data and ML pipelines and compute engine.”

“Semantic Graph:
The rich semantic layer allows diwo to capture the complete business context by embedding business and data definitions, correlations among them, KPIs and best practices.”

“In-Memory Computing:
Compute engine which continually senses trends in incoming data to uncover new opportunities and explores correlations among the outputs of AI/ML, optimization and simulation models to produce the most informed recommendations.”

“Knowledge Object Store:
Comprehensive database that includes detailed data from all designated operational sources, synthesized within diwo, and provides a complete baseline for observations and recommendations.”

“Data and ML Pipelines:
Deep learning algorithms that ensure continuous learning and observations that empower users to identify immediate risks and opportunities for growth.”

“GUI to User Interface:
A simple, natural language interface presents results and recommendations in the user’s context, masking the underlying complexity and making it easy for decision makers to understand, interact and act.”

How does diwo compare?

Data-centric perspective vs Decision-centric perspective differences

How does diwo compare?

Data-centric perspective vs Decision-centric perspective differences

Augmented decision-making capabilities are created through a man-machine symbiotic system in a cognitive framework we call SEAL: Sense, Explore, Act, and Learn.

Sense

Data from internal and external sources are continuously analyzed on multiple levels to expose patterns and fluctuations that could indicate opportunities. diwo automates this process by linking to data sources and analyzing them to continuously sense, synthesize, and present predefined opportunities before they occur.

Explore

A combination of predictive, prescriptive, and optimization methods are used to analyze and recommend an optimized strategy for addressing sensed opportunities.

Act

The result? Every user receives suggestions for actionable guidance with real-time insights, in an easy-to-understand contextual format. Working with multiple strategies, diwo guides users towards the best game plan and instructs them step by step. The interface provides an intuitive user experience, even quantifying the user’s adjustments in real-time.

Learn

diwo’s Artificial Intelligence capabilities allow it to learn and assimilate decisions continuously. diwo grows as it learns, constantly improving its prediction accuracy and sensing speed. It also optimizes the user’s experience, by learning from user input and assessing the impact of past actions on business performance.

Augmented decision-making capabilities are created through a man-machine symbiotic system in a cognitive framework we call SEAL : Sense, Explore, Act, and Learn.

Sense

Data from internal and external sources are continuously analyzed on multiple levels to expose patterns and fluctuations that could indicate opportunities. diwo automates this process by linking to data sources and analyzing them to continuously sense, synthesize, and present predefined opportunities before they occur.

Explore

A combination of predictive, prescriptive, and optimization methods are used to analyze and recommend an optimized strategy for addressing sensed opportunities.

Act

The result? Every user receives suggestions for actionable guidance with real-time insights, in an easy-to-understand contextual format. Working with multiple strategies, diwo guides users towards the best game plan and instructs them step by step. The interface provides an intuitive user experience, even quantifying the user’s adjustments in real-time.

Learn

diwo’s Artificial Intelligence capabilities allow it to learn and assimilate decisions continuously. diwo grows as it learns, constantly improving its prediction accuracy and sensing speed. It also optimizes the user’s experience, by learning from user input and assessing the impact of past actions on business performance.