Enterprise-scale

Algorithmic Scale is Different

Enterprise scale goes beyond compute. Here's why:

Math is hard

Math is far more difficult to scale than servers. The result is that most approaches  “downgrade” or simplified their algorithms to run against larger and larger datasets. Ayasdi has invested significant resources to deliver enterprise-class workload management to ensure its math scales with the size of the challenge.

Adaptability is key

Your existing IT system won’t bend to your AI needs – it is the other way around. This means Active Directory for User Management, leveraging existing data lake infrastructure, and respecting the security and compliance guidelines for operational systems. Ayasdi works seamlessly with Hadoop and other architectures to ensure AI can run anywhere, anytime.

Exceptional user experiences required

Enterprise scale requires exceptional user experiences. This is more than Excel, PDF, or PowerPoint. Enterprise scale demands that AI go to market in the form of well-designed applications that put the user experience first, ensuring these powerful technologies are adopted broadly.

Collaboration matters

To accelerate the creation of workflows between line of business, data science, and IT you need a framework for application development that delivers powerful technologies in the right application package, in the right places, solving the right problems – automatically.

These are all elements that Ayasdi focuses on and what we mean when we talk about enterprise scale. They come from our experience in dozens of enterprise-grade deployments – not just pilots or POCs.

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