About Keebo

Keebo provides a fully automated optimization platform for Snowflake, utilizing patented technology to dynamically adjust warehouse size, clustering, and memory based on real-time workload changes. This solution reduces operational costs by at least 25% without compromising query performance, freeing up data teams from manual oversight.

```xml <problem> Companies using Snowflake often face challenges in optimizing their data warehouse spend due to the dynamic nature of workloads and the complexities of manual tuning. Inefficient warehouse sizing, clustering strategies, and memory allocation can lead to unnecessary costs and underutilized resources. </problem> <solution> Keebo offers an automated optimization platform for Snowflake that dynamically adjusts warehouse size, clustering, and memory allocation based on real-time workload analysis. The platform leverages patented AI technology to identify and implement cost-saving opportunities without impacting query performance. By continuously monitoring telemetry metadata, Keebo automatically adapts to changing workload patterns, ensuring optimal resource utilization and minimizing wasted spend. The solution provides full visibility into its optimizations, allowing users to verify savings and maintain control over their Snowflake environment. </solution> <features> - Automated warehouse resizing based on real-time workload analysis - Dynamic adjustment of clustering and memory allocation for optimal performance - Patented AI algorithms that learn and adapt to changing workload patterns - Real-time performance protection with automated "backoffs" during workload spikes - Full visibility into optimizations and savings through a user-friendly portal - Customizable rules and conditions for fine-grained control over optimization strategies - Secure connection using only telemetry metadata, with support for SSO and PrivateLink - Detailed savings reports and Snowflake spend analysis </features> <target_audience> Keebo is designed for data teams and organizations using Snowflake who are looking to reduce their cloud data warehousing costs and improve resource utilization without sacrificing query performance. </target_audience> <revenue_model> Keebo offers two pricing options: a commission-based model where customers pay a percentage of the savings achieved, and a flat-rate model based on annual spend, number of warehouses, and estimated savings. </revenue_model> ```

What does Keebo do?

Where is Keebo located?

Keebo is based in Palo Alto, United States.

When was Keebo founded?

Keebo was founded in 2019.

How much funding has Keebo raised?

Keebo has raised 19000000.

Location

Palo Alto, United States

Founded

2019

Funding

19000000

Employees

47 employees

Major Investors

True Ventures

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Keebo

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Executive Summary

keebo.ai 3K+

Crunchbase

Founded 2019 – Palo Alto, United States

Funding

Estimated Funding

$10M+

Major Investors

True Ventures

Team (40+)

No team information available.

Company Description

Problem

Companies using Snowflake often face challenges in optimizing their data warehouse spend due to the dynamic nature of workloads and the complexities of manual tuning. Inefficient warehouse sizing, clustering strategies, and memory allocation can lead to unnecessary costs and underutilized resources.

Solution

Keebo offers an automated optimization platform for Snowflake that dynamically adjusts warehouse size, clustering, and memory allocation based on real-time workload analysis. The platform leverages patented AI technology to identify and implement cost-saving opportunities without impacting query performance. By continuously monitoring telemetry metadata, Keebo automatically adapts to changing workload patterns, ensuring optimal resource utilization and minimizing wasted spend. The solution provides full visibility into its optimizations, allowing users to verify savings and maintain control over their Snowflake environment.

Features

Automated warehouse resizing based on real-time workload analysis

Dynamic adjustment of clustering and memory allocation for optimal performance

Patented AI algorithms that learn and adapt to changing workload patterns

Real-time performance protection with automated "backoffs" during workload spikes

Full visibility into optimizations and savings through a user-friendly portal

Customizable rules and conditions for fine-grained control over optimization strategies

Secure connection using only telemetry metadata, with support for SSO and PrivateLink

Detailed savings reports and Snowflake spend analysis

Target Audience

Keebo is designed for data teams and organizations using Snowflake who are looking to reduce their cloud data warehousing costs and improve resource utilization without sacrificing query performance.

Revenue Model

Keebo offers two pricing options: a commission-based model where customers pay a percentage of the savings achieved, and a flat-rate model based on annual spend, number of warehouses, and estimated savings.