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AI-Powered Smart Aggregation Technology

Enhance BI performance and reduce costs with our patented technology built for performance, speed and scale.

Intelligent Data Modeling

Scalable Analytics

Elastic Architecture for Savings

High-Performance Queries

Built for the Cloud

Conversational Analytics

Benefits of GenAI Powered Aggregation Technology

  • – Supercharged analytics with high query performance at massive scale
  • – Simplified data modeling to map complex business use cases
  • – AI-based smart aggregation and intelligent caching to reduce querying costs
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Modern analytics features

From simplified analytics and a single source of data for LLMs to standardized data interpretation, our semantic layer acts as a critical building block of a modern data and AI stack.

Complex Hierarchies

Complex hierarchies including ragged, unbalanced, recursive, and alternate hierarchies, and custom rollups.

Distinct Count

Accurate distinct count on billions of rows.


Support for multi-fact, star, snowflake, and other schema designs, as well as additive and semi-additive functions.

Elasticity and Auto-Scaling 

Schedule clusters to scale up and down to deal with predictable load changes without disruption.

Incremental Data Refreshes 

Scheduled and automated data refresh feature for adding and replacing data in data models quickly without coding or manual intervention.

Intelligent Caching

Advanced caching features - auto-population, purge, and repopulation. Multi-level caching based on query patterns and analysis of data models.

UI-Based Data Modeling 

AI-assisted, code-free visual designer to define relationships between datasets using simple drag-and-drop operations.

High-Performance Analysis 

Workflow-based quick analysis to design an OLAP database model with minimal interaction and bootstrapping work.

How Is Kyvos Better Than Legacy OLAP

Legacy OLAP


Kyvos’ AI-Powered Aggregation

Deteriorates with scale and concurrency.


Sub-second responses for queries.

Limitation on the amount of data in a single cube.


Create data models on billions of rows.

Slows down for higher concurrencies.


Thousands of concurrent users.

Manual tuning is required to decide which aggregates to create.


ML-powered intelligent aggregates and caching.

Cube build takes longer and consumes more resources as data size increases.

Cube Building

Quick and easy processing of data models.

Built for on-premises. Has to be retrofitted in the cloud.

Platform Support

Purpose-built for cloud platforms and cloud data warehouses. Also supports on-premise.


High-performance analytics on the cloud

Kyvos Analytics Acceleration Platform Architecture

Learning and Insights

Stay ahead of the curve

Whitepaper Cloud Analytics Kyvos Resources


High-speed data analytics on the cloud: Think big with modern OLAP



Leading telecom enhances 150 billion viewer interactions


The Hitchhiker’s guide to OLAP

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All roads lead to OLAP… Eventually

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