AWS bills Bedrock usage in aggregate. Keito attributes that model spend to client, project, and agent so AI inference cost becomes a defensible line in your billing instead of an unexplained AWS total.
Cost review
Bedrock spend tracked
$9.4k
Active work
24
Reviewed
91%
Ready to bill
$18.4k
Time captured with context
aws bedrock cost tracking
Billing review complete
Client and project checked
Invoice evidence ready
Approved summary prepared
aws bedrock 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.
Bedrock cost attribution
AWS Bedrock makes it easy to call foundation models from Anthropic, Meta, Amazon, and others through a single managed API, which is exactly why services teams are building client-facing AI features on it. The billing problem appears in the AWS console: Bedrock usage shows up as aggregate inference and token spend across the whole account, with no native sense of which client, project, or agent generated it. For an agency building AI workflows for several clients, that aggregate number is impossible to bill against. When a client asks what the AI portion of their invoice covers, or when finance wants to know whether an AI feature is margin-positive, there is no attribution layer connecting Bedrock spend to the work that caused it. Keito provides that layer. Bedrock model usage is attributed to client, project, and agent alongside the human billable hours for the same work, so AI cost sits in the same billing record as everything else. Costs can be reviewed before they reach a client report, marked up or passed through according to the engagement, and explained in client-readable summaries. Instead of a single opaque AWS figure, each client sees the Bedrock spend their work actually generated — and the agency can see AI margin per engagement.
Attribute Bedrock inference and token spend to client, project, and agent
Review AI cost alongside billable hours before client reporting
Turn an aggregate AWS total into defensible per-client AI cost lines
Workflow fit
Keito keeps aws bedrock cost tracking connected to client, project, billable status, approval, and invoice context before the work reaches finance.
Attribute Bedrock inference and token spend to client, project, and agent
Review AI cost alongside billable hours before client reporting
Turn an aggregate AWS total into defensible 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 AWS bill vs per-client attribution
Keito keeps aws bedrock 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 aws bedrock 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 aws bedrock 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.