Google Cloud bills Vertex AI usage in aggregate. Keito attributes that model spend to client, project, and agent so AI inference cost becomes a defensible billing line instead of an unexplained cloud total.
Cost review
Vertex spend tracked
$8.7k
Active work
24
Reviewed
91%
Ready to bill
$18.4k
Time captured with context
vertex ai cost tracking
Billing review complete
Client and project checked
Invoice evidence ready
Approved summary prepared
vertex ai cost tracking needs more than a timer. The billing record has to keep client, project, approval, and invoice context together before the work reaches finance.
Record token fees, subscription usage, and compute costs against the client project they serve as the agents run — not reconstructed at billing time from company card statements.
Combine AI agent cost records with human billable hours in one review so the total delivery effort is visible before the invoice cycle starts.
Use reviewed human and agent cost data to prepare client summaries and invoice backup that reflect how the work was actually delivered.
Vertex AI cost attribution
Google Vertex AI gives teams a managed way to run Gemini and other foundation models in production, and agencies are increasingly building client AI features on it. The billing gap is the same one every cloud AI platform creates: Vertex AI usage lands in Google Cloud billing as aggregate model and token spend across the project or account, with no native breakdown by the client, engagement, or agent that generated it. For a services firm running AI workflows for multiple clients, that aggregate figure cannot be billed or assessed for margin. When a client asks what the AI line on their invoice represents, or when a delivery lead wants to know whether an AI feature is actually profitable, there is no link between Vertex AI spend and the work behind it. Keito supplies that link. Vertex AI model usage is attributed to client, project, and agent alongside the human billable hours for the same engagement, so AI cost lives in the same reviewed billing record as everything else. Costs are reviewed before client reporting, marked up or passed through per the engagement terms, and explained in client-readable summaries. Each client sees the Vertex AI spend their work generated rather than an opaque Google Cloud total, and the agency sees AI margin per engagement instead of guessing.
Attribute Vertex AI inference and token spend to client, project, and agent
Review AI cost alongside billable hours before client reporting
Turn an aggregate Google Cloud total into per-client AI cost lines
Workflow fit
Keito keeps vertex ai cost tracking connected to client, project, billable status, approval, and invoice context before the work reaches finance.
Attribute Vertex AI inference and token spend to client, project, and agent
Review AI cost alongside billable hours before client reporting
Turn an aggregate Google Cloud total into per-client AI cost lines
Keito tracks AI agent costs against the same client and project structure as human billable hours so agent spend is never invisible overhead. Agent sessions land as source-tagged time entries via the CLI, API, or Agent Skill, with LLM token costs logged as expenses.
See total delivery cost — human hours and AI agent costs together — by client and project so pricing, margins, and billing decisions reflect the real cost of work.
Keito flat pricing means adding AI tracking capacity to the billing workflow does not create a per-seat cost spike as more people and more agents are involved in delivery.
The difference is not just recording time. It is whether the record can support billing, project decisions, and client conversations.
Aggregate cloud bill vs per-client attribution
Keito keeps vertex ai cost tracking tied to clients, projects, billable status, approvals, and billing summaries in one workspace.
Typical setups capture time in one tool and rebuild the billing explanation later from exports, comments, or spreadsheet cleanup.
Review before invoicing
Managers review entries before they become invoice evidence, so missing context is fixed internally rather than during a client dispute.
Raw timer exports usually reach finance before delivery leads have confirmed whether the work is billable, complete, or client-ready.
Predictable team pricing
Flat-rate plans let delivery staff, reviewers, contractors, and finance users participate without per-seat pricing friction.
Per-seat time trackers make teams choose between clean billing participation and controlling tool spend.
Use a workspace where time is captured against the right client and project, reviewed before invoicing, and exported as billing evidence. Keito is built around that workflow, so vertex ai cost tracking is not separated from the approval and invoice context it needs.
Yes. Keito tracks work by client, project, person, billable status, and review state, then turns approved records into client-ready summaries. That makes it useful when vertex ai cost tracking needs to support billing, profitability, and client reporting rather than just attendance.
A generic timer records duration. Keito records billable context: who did the work, which client and project it belongs to, whether it has been reviewed, and how it should appear in billing evidence.
Solo is built for one human owner and unlimited AI agents. Pro adds human teammates. Business adds integrations, exports, and online invoice payments.
One human owner
For independent consultants, freelancers, and small studios running work with AI agents.
Team collaboration
For teams that need shared workspaces, approvals, and team-level project visibility.
Advanced operations
For organizations that need integrations, exports, online payments, and stronger controls.
AI agents do not count as human seats on any plan.
Solo, Pro, and Business can use API keys for agent workflows.
Stripe payments, exports, Xero, and QuickBooks are on Business.
Start with Solo, add people on Pro when you need reviewers or collaborators, and see how Keito turns tracked effort into clearer reports.