Bedrock
AWS · Bedrock
Every Bedrock dollar, accounted for.
On-demand tokens, provisioned throughput, agents, and knowledge bases. One view of what your org spends on Bedrock, and what it produces.
Bedrock is one line in the AWS bill. Your FinOps tool sees usage types, not teams.
- Spend by team, model, and use case, without the tagging homework
- Model-mix visibility across the whole Bedrock catalog
- Cost per output: spend tied to work actually delivered
We’ll reach out at the email you provided.
TRUSTED BY AI-FORWARD ENTERPRISES
THE WHOLE STACK
Start with Bedrock. Measure everything.
Larridin measures AI spend across every vendor your org runs: Bedrock beside OpenAI, Claude, Cursor, and Copilot, plus the seats and subscriptions your cloud bill never sees.
- Every vendor, seat, and agent in one spend model
- Attributed by team, department, and use case
- One ROI number across the stack
EVERY VENDOR, ONE SPEND MODEL
Bedrock is one column in the ledger. Multi-cloud orgs see Azure OpenAI and Vertex AI land the same way, attributed to the same teams, departments, and use cases.
HOW IT ADDS UP
However your org buys AI, the spend lands in one place.
Consolidated first, then owned, then tied to output.
CONSOLIDATE
The whole AI bill, reconciled
Cloud-billed tokens, seats, credits, and subscriptions from every vendor: one spend model across the stack.
ATTRIBUTE
Each dollar gets an owner
AWS attribution bottoms out at usage types per day, and only after you build the tag scaffolding. Larridin maps Bedrock spend to teams, departments, and use cases from your org chart.
PROVE ROI
Spend meets the work it paid for
Cost per output, hours returned, unit economics per workload: measured from the work itself, ready for the budget review.
FULL BEDROCK COVERAGE
Bedrock spend is not even all in Bedrock: Marketplace models bill as SageMaker, vector stores as OpenSearch. Larridin reads the whole bill. Running Claude on Bedrock? The Claude page covers the Anthropic side.
WHAT IT PRODUCED
Bedrock spend, tied to work delivered.
Unit economics per workload, measured from the work itself. The budget review starts with a number, not a usage-type export.
- Cost per resolved ticket, per document, per PR
- Claude Code on Bedrock, priced per developer
- Workload trends by team and use case
Bedrock ROITHE BEDROCK LEDGER
Usage types in. Teams and models out.
Cost Explorer speaks in usage types per day. Larridin turns the same data into spend by model, team, and use case, with the side-costs counted.
Bedrock SpendAll your AI spend, Bedrock and beyond, in one place. Attributed by team, department, and use case.
We’ll reach out at the email you provided.
ATTRIBUTION
Attribution without the homework.
AWS’s answer is one inference profile per model per team, tags activated in Billing, and every app rewritten to call new ARNs. Larridin reads your billing exports and maps spend to teams from the org chart instead.
- No inference profiles to create, no apps to rewrite
- Works behind LLM gateways, where IAM attribution stops
- Unattributed spend flagged, with the workloads behind it
PROVISIONED THROUGHPUT
Idle model units burn at full price.
Provisioned throughput bills hourly whether traffic comes or not, and committed terms run to term. Larridin shows utilization against each commitment, so the next term is sized from evidence.
- Utilization per commitment, tracked daily
- Idle-hour cost priced, not buried in the bill
- On-demand vs. committed, compared per workload
ONE VIEW
Take one screen into the budget review.
Every vendor’s spend, next to the work it produced. Bedrock in context.
Output attribution. Work delivered across the stack, measured from the systems it lands in, beside what it cost.
Every vendor, one column each. Bedrock sits beside the direct APIs and the seat products, so the budget conversation covers the whole stack.
Bedrock in context. The line inside the AWS bill, measured against everything else you run.
HOW IT CONNECTS
Connected in a day.
Connect AWS
Point Larridin at your cost and usage exports. No inference profiles to create, no apps to rewrite.
Allocation syncs
Accounts, tags, and callers map to teams and cost centers from the org chart you already maintain.
Output attaches
Work delivered by Bedrock workloads lands next to what it cost: cost per output from the first scan.
FAQ
Questions Bedrock customers ask us.
How do I break down AWS Bedrock costs by team or application?
Natively: one inference profile per model per team, tags activated in Billing, and apps rewritten to call profile ARNs, none of it retroactive. Larridin maps your billing exports to teams, departments, and use cases from the org chart instead.
Why doesn’t my token math match the Bedrock bill?
Bedrock prices four token types separately, with different rates per service tier and per routing type. Miss cache reads or cross-region suffixes and the numbers drift. Larridin reconciles against the bill itself.
Is Claude cheaper on Bedrock or on the Anthropic API?
On-demand token prices are broadly the same; what differs is billing mechanics and visibility. Larridin shows both channels side by side, so the choice is about operations, not guesswork.
Can I cancel a provisioned throughput commitment?
No. Committed terms run to term, whether the model units are busy or idle. What you can do is track utilization against each commitment and size the next one from evidence.
Why is my Knowledge Base costing money with no traffic?
The vector store behind it usually is: OpenSearch Serverless carries a capacity floor that bills around the clock, outside the Bedrock service line. Larridin counts those side-costs as part of the workload.
How do we measure ROI on Bedrock spend?
Unit economics from the work itself: cost per resolved ticket, per document, per PR, measured per team and workload. The budget review starts with a number.
CHEAP TOKENS AREN’T THE GOAL
Useful ones are.
Optimize cost per outcome.
Larridin ties model spend to the work it produced, so you optimize for cost per outcome, not cost per token.
We’ll reach out at the email you provided.
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