Description
Keebo provides autonomous optimization for cloud data warehouses, specifically targeting Snowflake and Databricks. Its core technology utilizes agentic AI and workload intelligence to continuously tune data warehouse performance and efficiency without requiring manual intervention, query rewriting, or risking Service Level Agreements (SLAs).
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This automated approach aims to maximize the value of data cloud investments by delivering predictable performance and accelerating engineering velocity. Keebo's system continuously monitors warehouse settings, including warehouse size, auto-spend time, and cluster count, making dynamic adjustments in real-time. It also incorporates performance protection layers, automatically reverting to default settings during workload spikes or increasing query queues to maintain stability.
Beyond autonomous optimization, Keebo offers comprehensive data platform observability and reporting. This provides full visibility into query behavior, bottlenecks, and inefficiencies, enabling data and FinOps teams to identify optimization opportunities and align their strategies. The platform is designed to be transparent, allowing users to monitor, control, and verify all optimizations, ensuring they remain in charge of their data infrastructure.
Keebo is positioned as a pioneer in fully autonomous data cloud optimization, differentiating itself from tools that only offer visibility and reporting. It aims to accelerate innovation by minimizing operational overhead, reclaiming hundreds of hours monthly that would otherwise be spent on manual optimization. Customers have reported significant cost savings, with an average verified cost reduction of 27% and specific instances of 50% to 70% savings on application usage.
The setup process is designed to be straightforward, taking approximately 30 minutes with guided assistance. Keebo integrates with existing authentication methods like Keebo accounts or Okta SSO and requires access only to specific Snowflake and Databricks usage metadata fields that users control. This focus on ease of use and control makes Keebo an attractive solution for modern data teams looking to enhance efficiency and reduce costs in their data cloud environments.
- CategoryAI Data Analysis
- DeploymentCloud
- PlatformsWeb
Keebo's Core Features
Autonomous data warehouse optimization for Snowflake and Databricks
Agentic AI for real-time warehouse tuning
Workload intelligence for performance insights
Automated cost savings averaging 27%
Five layers of performance protection
Reclaims hundreds of hours of engineering time monthly
Full data platform observability and reporting
Continuous monitoring of warehouse settings (size, clusters, auto-spend)
Automated 'backoffs' to default settings during workload spikes
Fine-grained control over optimization application and timing
Audit trail for all optimization actions
User-configurable optimization aggressiveness via slider bar
How to use Keebo?
Connect Data Warehouses: Link Keebo to your Snowflake and Databricks accounts.
Configure Access: Grant necessary metadata access for monitoring and optimization.
Set Optimization Preferences: Define control parameters and desired aggressiveness.
Monitor Performance: Observe real-time optimizations and cost savings.
Review Audits: Verify actions taken by Keebo and your team.
Keebo's Use Cases
- Cost Reduction
- Performance Improvement
- Engineering Efficiency
- Autonomous Tuning
- Data Cloud Management
- FinOps Alignment
