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10X Speed. 10X Savings. 10,000x Insights.

Google and Aible makes analytics and data science faster, cheaper, and more insightful. With end-to-end serverless architecture and a unique approach to augmented analytics and data science, the collaboration brings time to results down from months to minutes, offers a 1000x reduction in server costs, and automatically analyzes millions of valuable combinations compared to hundreds that a human analyst can explore.

1000x Savings With End-to-End Serverless

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Aible and Google bring serverless architecture to realize significant cost efficiencies for analytics and data science initiatives. Where a typical project may run for 4-6 months, requiring thousands of hours of server up-time, Aible actively conducts ‘analysis’ activities for just a few minutes - translating to more than a 1000x reduction in server time. Added to that, Aible’s serverless model training is also x3 more cost-effective than the same analysis on comparable servers, according to this benchmark by Intel and Aible.

Speed and Cost of Analysis Benchmark at a Fortune 500 Company

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At a Fortune 500 enterprise, 75 datasets with over 100M rows were evaluated with Aible on BigQuery, without any special optimizations. In only 2 weeks, over 150 million variable combinations were analyzed and the total cost across all that evaluation was just $80.

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Secure. Transparent. Trusted.

When Aible needs to evaluate data, transform it, analyze it, or create predictive models, it pushes the relevant queries to the customer’s own private BigQuery or BigQueryML as appropriate. It then saves the relevant metadata (including analysis results and models) in the customer’s own private Google cloud account. Whenever a user interacts with the analysis results or models, all of the work is done in their browsers, and the metadata is securely accessed as necessary. Aible never gets access to their data, which remains secure in the customer’s own private Google account.

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Proven Success

Overstock.com used Aible to improve speed to data-quality evaluation from weeks to minutes per dataset. The entire Aible project took just 5 days, including installation and integration with Overstock's BigQuery to Executive review and acceptance of results. Read Full Success Story.

Impact in 30 Days. Real-world Case Studies

Use Case: Sales opportunity prioritization

Duration: 20 days

Results: Actionable insights
on sales opportunities

Use Case: Identify insights from
Social Determinants of Health (SDoH)

Duration: 15 days

Results: 20X improvement in speed
to insight

Use Case: First-time in college
student retention

Duration: 15 days

Results: 17% reduction in student attrition