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Geminos Causeway is an end-to-end low code platform for modeling, building and deploying Causal AI applications.

Our model-first approach helps businesses understand their problem domains in a way that can be easily communicated and refined with data scientists and domain experts.

Guided analysis and validation of the causal odels helps remove issues like bias before hydrating ith real data.

ETL models can be implemented to deliver instant predictions and deployable AI applications.

Model First Approach

Utilize Causal and Knowledge models to capture and communicate real-world problems and data with stakeholders

Built on Open-Source

Our enterprise-scale platform is
built on a battle-tested technology stack including Node-RED
and TypeDB

Causal Libraries

Causal ML libraries packaged as standard include MS DoWhy & EconML, CausalML plus more being added in future releases

End-to-End Solution

From model to data analysis and deployment within one platform, Causeway allows you to iterate your models and redeploy

Supports Your SDLC

Support for model reuse, project workspaces, team workspaces and integration with source code control in a flexible environment

3,800+ Integrations

Drag and drop from a library of connectors to seamlessly integrate with your data or IoT landscape

Causality Has the Answer

Thinking about the world, or more importantly your problem domain, in terms of cause and effect resolves many of the challenges faced with traditional machine learning.

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Common Language

Capturing the scope of your problem domain through causal modeling provides an easy way to collaborate within your team and business. Geminos Causeway provides a multi-user platform to collaborate across the business and capture domain knowledge is a simple intuitive way.

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Reduced Bias and Fair

The science of causal algebra has causal analysis and validation built in to eradicate bias. Geminos Causeway gives you access to these powerful techniques without having to worry about math.

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Adaptive to Change

Because of Causeways end-to-end traceability
(model <> application), changes to the causal model can be rippled through data to the AI implementation and visa-versa. This process is facilitated through the Causeway platform.

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Explainable

AI solutions built using causality are intrinsically explainable through the causal models. There is absolute traceability from each event to related data and ultimately AI functions and predictions.

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Human-Centric

Rather than limiting human-machine interaction, Causal AI allows a tighter partnership and sharing of knowledge

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Small or Large Datasets

Geminos Causeway can apply its discovery algorithms to only the information that matters, even small amounts of data. Coupled with human input, it can fill in gaps in data to work with any kind of dataset, big or small.

 

Features

Causeway Research
for Academic Institutes
M O S T    P O P U L A R
Causeway
Team

for Data Science Teams
Causeway Enterprise
for Organisational Deployment
Multi-User
Delivered as SaaS or on Public and Private Cloud
Unlimited Users1 1 To 49 Users 50+ Users
Deployment
Accessed as a SaaS web service or deploy on your existing cloud
Cloud2 SaaS or Cloud2 SaaS or Cloud2
Causal Modeling
Capture causal relationships, treatments, and outcomes. Abstract complexity
Model Validation
Causal model analytics. Highlighting bias
Knowledge Modeling
Link causal models to data enabling causal analysis
Library Re-Use
Share models, functions, flows with your team / organisation
Data Connectivity
Connect to multiple data sources easily, including: CSV, MS SQL, MySQL, ODBC, TensorFlow, IoT, etc.
Deployable AI
Execute models in test or production environments
Integrations Included
Free plugins available to access your stack and environments
3,500+ 3,500+ 3,500+
Bespoke Integrations
Drag-and-drop your own R Script, Python, Java, C#, etc. libraries
$499 per faculty/month
unlimited research transactions
$99 per user/month unlimited test transactions
$POA per deployment transaction
$POA per user/month
unlimited test transactions
$POA per deployment transaction

1. Unlimited research seats per faculty to allows researchers, lecturers, and students to create and share models
2. Cloud container deployments can be implemented in VMWare, AWS, GCP, IBM and Oracle. Other implementations are available, please enquire

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