Bring actionable recommendations to your business.

Seamlessly surface recommendations to your business partners as expressive, tailored and interactive applications focused on decision-making.

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Meet Dara

We have open sourced the core framework

Open Source Project

Fast and Simple AI App Development

Translating data science output for business use has never been easier.

decisionOS allows you to build production ready applications to power decision making using Causal AI in pure Python. Expressive interfaces can be created from minimal code, while application development is batteries included: there is no configuration required and a library of existing applications and components to select from accelerates your time to value.

config.add_page(
	title='Causal Graph',
        content=CausalGraphViewer(
  	    causal_graph=causal_graph,
     )
)

Embedded Decision Intelligence

Move beyond dashboards. Self-service recommendations instantly.

Out of the box components for embedding Causal AI powered decision intelligence capable of: scenario planning, recourse, fairness, effect estimation, and root cause analysis. Allow your application users to explore and generate recommendations while building trust through interpretability and explainability.

config.add_page(
	title="Business Recommendation',
            engine=Resource(
		model=model,
		data=data,
     )
)

Tight Integration with Jupyter

Elevate your notebook experience.

Use decisionOS to develop interactive components directly within Jupyter and render them inline, allowing for advanced and tailored exploration of phenomena seamlessly. Different skill sets within organizations can lead to friction and communication barriers. decisionOS helps you to overcome these challenges by providing native APIs to push data and context between notebooks and apps- enabling rapid collaboration between disparate groups.

decisionApp Building Features

Pure Python
Native Development
Instant Deployment
SSO Support
Inline Jupyter Rendering
Scalable Compute Backend
Catalogue of Templates and Examples
Enterprise Integrations

Frequently Asked Questions

What sort of skills do I need to create a decisionApp?

decisionApps are fully functional web applications written in pure Python. Therefore all you need to know is how to write Python!

How long does it take to get a decisionApp into production?

Development of decisionApps occurs natively on decisionOS without any local configuration, meaning that as soon as you are done developing an application it is immediately deployed onto the infrastructure. The result is a seamless transition from development to production with zero delay.

Why would I use decisionOS over Streamlit or Dash?

Streamlit and Dash are extremely capable tools for generating dashboards and showcasing work, however decisionOS apps have direct integration with Causal AI and causal drivers. decisionOS applications have integration with databases and downstream enterprise systems, as well as enterprise security features, to ensure that recommendations can be actioned securely. Furthermore, decisionOS has dedicated components for rendering causal graphs and models – enabling explainability and allowing trust to be built with the end user.

Ways to get started