About Keebo.ai
Keebo delivers AI-powered optimization for Snowflake and Databricks, helping organizations maximize cost savings, improve performance, and simplify cloud data warehouse management.
Keebo’s patented platform continuously learns from real-time metadata to autonomously optimize warehouses, queries, and workloads – saving you money while maintaining peak performance. This differs from CapitalOne Slingshot in one key way. CapitalOne Slingshot creates schedules that require human oversight and approval. Keebo’s algorithms constantly monitor and adjust your settings and require no human oversight.
Key capabilities include:
- Autonomous warehouse optimization for Snowflake and Databricks that right-sizes, suspends, and tunes clusters with minimal user effort.
- Workload intelligence and insights to give you deep visibility into spend, query performance, and resource usage.
- Smart query routing that dynamically directs queries to the best warehouse in real time to reduce costs and avoid congestion.
Setup is simple – usually under 30 minutes – and requires no advanced cloud or Snowflake expertise. Keebo accesses only metadata to ensure security and offers 24/7 support to keep your environment running smoothly.
About CapitalOne Slingshot
CapitalOne Slingshot was founded in 2022 based on Capital One’s need to manage spend across 50 separate business units & snowflake accounts. The tool was designed for CapitalOne’s own internal use cases and then released as product later. The tool focuses on governance features required by large banks to streamline access requests as well as cost monitoring. CapitalOne Slingshot can help some customers lower Snowflake spend by providing them with scheduled downsizing of their oversized warehouses on nights and weekends at the customer’s own risk (customer has to ensure the scheduled downsizing will not negatively impact their performance-sensitive applications).
Detailed Comparison
Autonomous Warehouse Optimization
| Capability | Keebo | CapitalOne Slingshot |
| Autonomous warehouse size adjustments | yes | no |
| Autonomous warehouse cluster-count adjustments | yes | no |
| Autonomous warehouse autosuspend adjustments | yes | no |
| Autonomous proactive suspension of idle warehouses | yes | no |
| Independently verifiable savings calculation | yes | no |
| Algorithm aggressiveness tuning | yes | no |
| Performance Guardrails (guarantees about max latency, 99th percentile latency, queue size, etc…) | yes | no |
| Outside change detection (automated detection of changes made by other applications and users to prevent overriding those settings) | yes | no |
| Custom schedule based resizing rules | yes | yes |
| Automated upsizing (if desired by users) | yes | no |
| Complete visibility into performed optimizations | yes | yes |
| Full control over which Snowflake warehouse settings are optimized | yes | yes |
| Governance and audit logs for user and system actions | yes | no |
Cost Visibility & Allocation
| Capability | Keebo | CapitalOne Slingshot |
| Out of the box spend dashboards | yes | yes |
| Connect multiple Snowflake accounts | yes | yes |
| Analyze query performance by warehouse | yes | yes |
| View savings on the UI | yes | yes |
| Analyze costs by warehouse | yes | yes |
| Analyze costs by Snowflake user | yes | no |
| Analyze costs using Snowflake tags | yes | yes |
| Analyze costs by Snowflake role | yes | yes |
| Projected Snowflake Usage | yes | yes |
| Projected savings | yes | yes |
| Budget based alerts | no | no |
| Cost spike alerts | Coming soon… | yes |
Performance Monitoring
| Capability | Keebo | CapitalOne Slingshot |
|---|---|---|
| Analyze query queuing by warehouse | yes | yes |
| Analyze data spillage by warehouse | yes | no |
| Analyze query queuing by warehouse | yes | no |
| Analyze query imbalance by warehouse | yes | no |
| See historical query performance | yes | no |
| See historical query stats (data scanned, pruning efficiency, spillage, etc.) | yes | no |
| Wasteful Queries Analysis (frequently failing) | yes | yes |
| Predefined alerts | yes | yes |
| Custom Alerts | Coming soon… | no |
Savings and Performance Recommendations
| Capability | Keebo | CapitalOne Slingshot |
| Underprovisioned warehouse recommendations | yes | yes |
| Query migration recommendation and Analysis (imbalanced warehouse) | yes | no |
| Memory inefficient recommendation (sub-optimal default autosuspend values) | yes | no |
| Unused tables recommendation | yes | yes |
| Rarely used tables recommendation | yes | yes |
| Workloads with high spillage | yes | yes (for jobs) |
| Most expensive queries | yes | yes |
| Query optimization recommendations | yes | yes |
Query Routing
| Capability | Keebo | CapitalOne Slingshot |
| Product maturity | 6 years (2019) | 3 years (2022) |
| Supported Platform | Snowflake, Databricks,(+ private preview for BigQuery) | Snowflake, Databricks (through recent acquisition of Sync Computing |
| Autonomous query routing | yes | no |
| Custom routing rules | yes | no |
| Metric based routing rules | yes | no |
| Optimize for KPIs (Average query latency, cost, etc… | yes | no |
Platform
| Capability | Keebo | CapitalOne Slingshot |
| SOC 2 compliance | yes | yes |
| Role-based access controls | yes | yes |
| Open API | yes | no |
| SSO portal access | yes | yes |
| Connect multiple Snowflake accounts | yes | yes |
Pricing
Keebo.ai offers flexible, customer-centric pricing to suit various business needs. Customers can choose between pay-for-savings, where payment is based on measurable savings, or a predictable flat-rate subscription. Success-based pricing ensures that Keebo’s objectives are closely aligned with those of its customers, as they are linked to generating measurable and demonstrable outcomes.
Capital One has not released details regarding CapitalOne Slingshot pricing. According to customer feedback, Slingshot uses a fixed-fee model. As it is not directly savings-based, CapitalOne Slingshot incentives are not inherently linked to the reduction of your Snowflake costs; rather, they maintain that the value is derived from the cost insights and optimization recommendations on which customers choose to act.
Frequently Asked Questions
Keebo is an AI agent that automatically optimizes Snowflake. It maximizes savings and ensures performance without manual intervention, offering a complete solution for efficient Snowflake environment management.
| Benefit Category | Specific Benefit | Description |
|---|---|---|
| Cost savings | Automatic cost reduction | Real-time, intelligent warehouse right-sizing, autosuspend tuning, and cluster-count optimization to slash costs without manual guesswork. |
| Verifiable savings | Guarantees savings backed by actual Snowflake metadata, not estimates, showing real impact on spending. | |
| Cost allocation & visibility | Enables cost allocation and visibility across users, warehouses, roles, and tags, providing clear insights into spend for finance and engineering teams. | |
| Performance protection | Custom SLAs & guardrails | Protects performance by setting limits on latency, queue size, and more, ensuring cost reductions don’t compromise query speed or reliability. |
| Dynamic query routing | Reroutes queries dynamically with custom rules aligned with KPIs, optimizing both cost and performance at the workload level. | |
| Control & transparency | Full control & governance | Allows users to choose which settings are optimized and when, with built-in audit logs, notifications, and complete governance transparency. |
| Total optimization visibility | Provides clear logs and explanations for every optimization action, ensuring users are always informed. | |
| Adaptability | Instant adaptation | Detects manual updates in Snowflake and adjusts automatically to keep optimizations on track. |
Keebo brings together full-stack automation, actionable recommendations, and intelligent query routing, delivering savings, speed, and assurance other platforms can’t match.
Keebo and CapitalOne Slingshot both offer automated warehouse optimization to reduce Snowflake costs, but Keebo delivers a smarter, more flexible, and more powerful solution. Slingshot relies on static schedules based on historical usage, requiring teams to review and approve each recommendation manually. That means missed savings windows and more engineering effort.
Keebo goes further by combining deep analysis with live response, optimizing continuously without waking your team up at 3AM.
Here’s how Keebo goes further:
| Autopilot or Approval-Only Mode | Keebo gives you full control, run in fully autonomous mode or opt for human-in-the-loop recommendations, depending on your comfort level. No rigid process. No constant handholding. |
| Real-Time, Autonomous Optimization | Keebo learns from live usage and adjusts size, autosuspend, cluster count, and upsizing instantly, no waiting, no schedules, no manual input. |
| Autonomous Query Routing | Keebo intelligently routes queries to the optimal warehouse to reduce queuing, cost, and latency, Slingshot doesn’t offer this capability at all. |
| Performance Guardrails | With six layers of safeguards, Keebo ensures no savings degrade performance, SLAs stay protected. |
| CFO-Verified Savings | Keebo calculates savings using your actual Snowflake metadata, so finance teams can trust the numbers, no inflated estimates or vague projections. |
| Full Governance & Visibility | Audit logs, user notifications, and granular control provide enterprise-grade accountability for every optimization decision. |
| Dynamic Change Detection | Keebo monitors for outside changes made in Snowflake and adapts automatically, ensuring continuous, drift-free optimization. |
| Insights + Recommendations | Keebo surfaces workload- and storage-based savings opportunities that go beyond what can be automated, helping your teams act with confidence. |
| Cost Allocation & Transparency | Track Snowflake spend by user, role, warehouse, and tag, giving your team and finance full clarity. |
Keebo delivers the next generation of FinOps automation, combining deep real-time optimization with smart routing, verified savings, and full enterprise control. Slingshot focuses on scheduled changes and manual recommendations, Keebo runs on autopilot with results you can measure, trust, and scale.
Keebo vs. CapitalOne Slingshot – Feature Comparison
| Capability | Keebo | CapitalOne Slingshot |
| Product Maturity | 6 years (2019) | 3 years (2022) |
| Autonomous Optimization | Fully autonomous, real-time AI-driven optimization | Scheduled adjustments; requires human oversight |
| Automation Flexibility | Autopilot or approval-only mode | Manual changes + fixed schedules |
| Performance Guarantees | 6-layer SLA protection | No guarantees |
| Savings Verification | Verifiable using your Snowflake metadata | Based on historical spend; may over-credit reductions |
| Pricing Alignment | Pay-per-savings or flat-rate subscription | Spend-based pricing |
| Smart Query Routing | Real-time, intelligent routing—no code or app changes required | Not supported |
| Governance & Audit Logs | Full logs, notifications, and user-level change tracking | Limited visibility |
| Change Detection | Reacts instantly to external Snowflake config changes | No change awareness |
| Actionable Insights | Surfaces cost and performance recommendations | Manual analysis required |
Commitment to Transparency
This comparison guide was created using publicly accessible information and customer feedback. If you find any errors, please get in touch with info@keebo.ai and include proof to support your correction request, and we will update the page.