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features
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support

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Write a Review

Description

Data Poem stands out as a leading Enterprise Decision AI firm, addressing the complexities faced by large organizations that often rely on numerous isolated models and dashboards that merely report past events without offering actionable insights. Its flagship product, POEM365, integrates these disparate systems into a cohesive causal framework, illustrating the relationships between various factors like spending, demand, and pricing as they influence revenue streams. With a robust foundation built on 250 billion transactions and an impressive five trillion dollars of spending data, the model can be implemented in approximately six weeks. Major brands within the Fortune 500 across sectors such as consumer packaged goods, retail, automotive, and e-commerce leverage this technology to enhance their revenue forecasts, budget planning, campaign optimization, and overall growth strategies. This transformative approach not only streamlines decision-making processes but also empowers organizations to adapt proactively to market changes.

Description

A no-code AI platform designed for enterprises transforms raw data into enhanced business insights. In the pursuit of valuable information within extensive data lakes, misleading correlations can contaminate findings, resulting in unreliable signals for organizations. CausaLake smartly identifies the most relevant data tailored to specific use cases, standing out as the sole technology capable of delving beyond correlated indicators in comparable datasets to pinpoint causal factors. Causal AI models illustrate the workings of various systems, encompassing economies, businesses, and biological entities. They offer a high level of trust and transparency, merging the strengths of human expertise with artificial intelligence. CausaLab represents the pinnacle of causal model discovery technology. The essence of AI transcends mere future predictions; it aims to actively influence outcomes. For AI to facilitate high-quality decision-making, it must grasp the human context alongside the goals and limitations of organizations. To address this challenge, we introduced decisionOS, which effectively connects predictions with actionable decisions, empowering organizations to optimize their strategies.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

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Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Data Poem

Founded

2019

Country

United States

Website

datapoem.ai/

Vendor Details

Company Name

causaLens

Country

United Kingdom

Website

www.causalens.com/causal-decision-making-ai-platform/

Product Features

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Decision Support

Application Development No 
Budgeting & Forecasting No 
Data Analysis No 
Decision Tree Analysis No 
Monte Carlo Simulation No 
Performance Metrics No 
Rules-Based Workflow No 
Sensitivity Analysis No 
Thematic Mapping No 
Version Control No 

Alternatives

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Alternatives

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