Attribute every cost to the team that owns it

Natural language queries. Describe what you want to see in plain language. AI resolves the accounts, tags, and services behind it automatically.

Untagged resource inference. Resources with missing or inconsistent tags attributed using AI inference across deployment history and service relationships.

Instant, zero-config results. Cost attribution views appear in seconds from your actual data. No spreadsheet exports, no tagging strategy needed.

Cost views for any team, service, product, or environment. Describe what you need in plain language. AI resolves the accounts, tags, and services behind it and builds the perspective automatically.

Untagged resources resolved through AI inference. Resources with missing or inconsistent tags are automatically attributed using AI inference across deployment history and service relationships.

Instant results with no manual configuration. Cost views appear in seconds from your actual data. No spreadsheet exports, no tagging strategy, no manual rules needed.

AI maps accounts, tags, and services to your actual business dimensions. Cloud accounts and services automatically mapped to your actual business dimensions: teams, products, environments, or whatever matters to you.

Categories update automatically as infrastructure changes. As your cloud footprint evolves, cost categories stay current without manual maintenance, rule updates, or re-configuration.

Shared costs allocated proportionally across owners. Shared infrastructure costs split intelligently across the teams and services that consume them, with a full audit trail for every allocation decision.

Pod- and namespace-level cost breakdown attributed per team and service. Every dollar of Kubernetes spend broken down to the namespace, pod, and label level across every cluster and cloud provider.

Works across EKS, GKE, AKS, and self-managed clusters. Consistent attribution methodology across every Kubernetes environment, regardless of cloud provider or cluster configuration.

Node cost allocation that accounts for bin packing and idle capacity. Bin packing overhead, idle nodes, and unallocated capacity shown as their own line items so waste is visible and actionable.

Per-customer cost breakdown across compute, storage, and data transfer. Every infrastructure dollar attributed to the customer, account, or segment responsible. Full breakdown by service type with no manual work required.

Identify high-cost accounts before they become margin problems. Automatic flagging when transfer costs or usage patterns create margin risk so you can act before the problem compounds.

Correlate infrastructure spend with revenue to surface true profitability. Join cost data with revenue signals to understand which customers are genuinely profitable and which need repricing or re-architecture.

Map infrastructure costs to product features and releases. Every cloud and AI dollar attributed to the feature that generated it, from compute to token usage to storage. No spreadsheet exports needed.

Compare feature cost against usage to identify low-value spend. Cost-per-active-user surfaced for every feature so product teams can prioritize based on real economics, not intuition.

Give product and engineering teams shared visibility into cost impact. A single source of truth for feature economics so product and engineering make decisions with the same cost data.

Team-level cost dashboards updated in real time. Per-team spend tracked continuously against budget. Every team sees their own costs without waiting for monthly finance reports.

Chargeback and showback reports for finance and leadership. Auto-generated chargeback reports on the first of each month. Exportable in any format for any internal billing model.

Trend alerts when a team is trending over budget before month end. Proactive alerts the moment a team's spend trajectory exceeds budget so leads can course-correct before month end.