Pricing
Not listed
Official monthly price not confirmed
- API
- Python audr and TypeScript @openaudr/audr SDKs; adapters and billing sinks documented.
AUDR
● Identity checkedAI usage infrastructure · Official vendor documentation reviewed 2026-10-07
AUDR is an open usage-record standard for attributing AI-agent infrastructure costs. It gives providers and developers a shared JSON format for identity, run, span and resource usage, with SDKs and adapter examples for capturing records and passing them to billing systems. It measures usage rather than providing a generative model.
- Category
- AI usage infrastructure
- Free access
- Apache-2.0 open standard and SDK code; infrastructure and billing services are separate.
- API access
- Python audr and TypeScript @openaudr/audr SDKs; adapters and billing sinks documented.
Is AUDR right for you?
A good fit for
Teams connecting multi-step agent runs to metered usage and billing records.
Before you choose
Requires instrumentation and a compatible sink. A shared run identifier helps attribution but does not establish final cost accuracy; validate schemas, aggregation and billing rates. No hosted-model entitlement is included.
Instrument a bounded agent run
Assign a run identifier, emit a record for each relevant operation and validate it against the schema. Compare joined usage with provider records before feeding a billing sink. Treat conformance fixtures as format validation rather than proof that an invoice is correct.
Open standard and billing handoff
AUDR’s specification and SDKs are Apache-2.0. Model tokens, gateway hosting, storage and billing platforms remain separate costs. Chargebee stewards the project; the PH launch title refers to this usage standard rather than a new generative Chargebee product.
What it can do
Features & capabilities
Unknown is different from unavailable. Each fact carries its own evidence.
| Capability | Value | Evidence | Checked |
|---|---|---|---|
| Standard | Version 1.0.0 usage record and JSON Schema Draft 2020-12. | Facts sourced | 2026-10-07 |
| Attribution | Run/span identity joins records from multiple metered operations. | Facts sourced | 2026-10-07 |
| Adapters | Examples cover LiteLLM, Vercel AI, Mastra and gateway integrations. | Facts sourced | 2026-10-07 |
| Data boundary | Records describe usage; the specification excludes prompts, key material and PII. | Facts sourced | 2026-10-07 |
Understand the total cost
AUDR pricing & plans
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Explore toolThe practical questions
Frequently asked questions
Does AUDR run an AI model?
No. It standardizes metered usage records from agent operations.
Do records contain prompts?
The official standard says prompt text, key material and PII are excluded from the usage record.
What is AUDR used for?
AUDR is an open usage-record standard for attributing AI-agent infrastructure costs. It gives providers and developers a shared JSON format for identity, run, span and resource usage, with SDKs and adapter examples for capturing records and passing them to billing systems. It measures usage rather than providing a generative model.
Does AUDR have a free plan?
Apache-2.0 open standard and SDK code; infrastructure and billing services are separate.. This record does not confirm an ongoing free plan.
How much does AUDR cost?
A listed monthly price has not been confirmed. See the plan cards for entitlements, billing commitments and seat minimums.
Can I use AUDR through an API?
Python audr and TypeScript @openaudr/audr SDKs; adapters and billing sinks documented.. API access and subscription access may have different terms; consult the linked sources.
What should I check before choosing it?
Requires instrumentation and a compatible sink. A shared run identifier helps attribution but does not establish final cost accuracy; validate schemas, aggregation and billing rates. No hosted-model entitlement is included.
Price history
No retained pricing changes yet. A current price alone does not establish a historical trend.
How this profile is supported
Official product documentation
Vendor website reviewed for current workflow and limitations; no application test performed.
Read original source ↗Facts apply to the named version and check date. Send a sourced correction if something changed.