Real-Time AI

More accurate, more powerful insights for every business

Real-time, AI powered apps need the right data, at the right time, to drive the biggest impact. Real-Time AI from DataStax, built on Apache Cassandra®, built for speed and scale.

Making Real-Time AI a Reality for All

Learn why real-time AI is critical for market-leading applications, and how all organizations can now build AI-powered apps.

Read the whitepaper

Bring the power of ML to your data

Explore how to accelerate the delivery of AI-powered apps, eliminate data transfer costs and access the right data at the right time.

Benefits

Build real-time,
AI-powered apps

More accurate predictions

Improve decision-making through deeper, more accurate insights into dynamically changing customer behavior, manufacturing operations, supply chain and more. Unique time-based approach enhances model accuracy and relevance to impact.

More accurate predictions

Optimized ML performance

Train models with the most up to date, accurate, real-time event datasets, synced with customer behavior and business operations.

Optimized ML performance

Simplified data engineering

Bring ML to real-time datasets, instantly ingesting data at massive scale without managing complex infrastructure and ops.

Simplified data engineering

Reduced costs

Start for free, eliminate data transfer costs by keeping data centralized, leverage market leading cloud economics.

Reduced costs

Improved data governance

Maintain raw data, features, and models in Astra to streamline regulatory processes, reuse and model optimization

Improved data governance

Leaders shaping their industries leveraging AI-powered apps

“In e-commerce, you must be able to instantaneously act on insights to provide customers with the most impactful experiences; and that requires the application of machine learning on real-time transactions. We have millions of customers using our website and mobile apps at any given moment and Astra DB is a powerful component of the Priceline data infrastructure. Our machine learning algorithms use massive data troves to provide valuable customer insights, greater personalization, and better travel recommendations, fueling our larger customer ecosystem.”

Martin Brodbeck
CTO at Priceline

“With DataStax and Apache Cassandra, we're able to serve real-time data to meet the expectations of our customers with less than 50 milliseconds of latency. At the same time, we can create 360-degree views of our customers and take advantage of AI/ML, which makes it easier to personalize experiences in today’s experience economy.”

Michael Palmer
CTO, US Bank

"We depend on DataStax Astra DB for the dynamic scalability and high performance we need to apply machine learning (ML) to real-time data. This means we can provide highly accurate, actionable insights for our clients and their customers."

Michael Cullum
CTO at Bud

"Liquid Analytics helps companies achieve their goal-based decisions with a real-time streaming analytics engine, Liquid Decisions. Astra DB gives us the performance and scalability objectives we require to deliver high-availability analytics for our customers.”

Vish Canaran
Data Science at Liquid Analytics

“The International Maritime Organization (IMO) has set a goal of cutting carbon emissions by 50% across the global maritime industry by 2050. Our SMARTShip platform is helping make this possible by leveraging DataStax Astra DB for AI-powered, predictive analytics. By transforming thousands of data points from some 40 major equipment systems on a typical ship in real time, our solutions enable vessel operators to optimize fuel costs and other operational parameters while advancing sustainability objectives.”

Praveen Viswanath
Co-founder and Enterprise Architect at Alpha Ori Technologies

“Our mission is to help every farmer grow healthier plants through AI/ML-powered, automated irrigation. Our high-resolution forecasts and soil moisture insights are backed by real-time data using DataStax Astra DB for accelerated performance.”

Revital Kremer
Chief Technology Officer at SupPlant

“Unlike many companies that claim emotional AI capabilities but only analyze words, Uniphore uses Computer Vision, Tonal and Natural Language Processing deep learning models to account for all modes of sentiment expression - facial expressions, tonal sentiment and the words that are spoken. We have about fourteen AI models that run in real time to coalesce the data into meaningful "read the room" for our clients. Without the ability to process data in real time, our solution really wouldn't be possible.”

Saurabh Saxena
Head of Technology and R&D

Resources

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