AI Suite Credits Definition
Updated: October 24, 2025
Please Note: Treasure Data may update these rates and terms from time to time in its sole discretion. Any such changes shall be effective immediately upon publishing to this webpage.
AI Suites
Purchased Credits may be redeemed for any of the metered entitlements shown below, at the rate of one (1) Credit for the number of entitlements shown (with proportionate consumption of fractional Credits):
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AI Suites Credit Consumption Ratios: 1 Credit |
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|---|---|---|---|
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AI Suite Meter |
AI Suite Availability |
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Personalization AI Suite |
Engagement AI Suite |
Creative AI Suite |
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100 Conversations |
✓ |
✓ |
✓ |
|
1 Million RT Profiles |
✓ |
✓ |
No |
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10 Million Personalization Calls |
✓ |
No |
No |
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15 Million Incoming Events |
✓ |
✓ |
No |
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25 Million Trigger Activations |
✓ |
✓ |
No |
|
1 Million Messages |
No |
✓ |
No |
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Calculation Examples: |
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AI Suite Meter Definitions:
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AI Suite Meter |
Definition |
|---|---|
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Conversations |
A Conversation is the basic metric of usage of Treasure Data’s AI Agent Foundry. A session that consists of 5 back-and-forth’s will be metered as a single Conversation using Treasure Data’s base Large Language Model, Claude 4.5 Sonnet. Shorter sessions will be metered as a fraction of a Conversation. For longer sessions, the metering rate (i.e., the ratio of back-and-forth’s to Conversations) will decrease below 5.0 if and to the extent the number of back-and-forth’s exceeds 5 (for example, a session with 10 back-and-forth’s would be metered as 2.87 Conversations). Conversations are metered on all Production Instances. |
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Real Time Profile |
A Real Time (RT) Profile is a collection of Core ICDP attributes and RT Attributes related to a single individual held in the Real Time Decision Engine. Each RT Profile may have up to a combined two hundred (200) Core ICDP attributes and RT Attributes, with a maximum size of 500 bytes per profile. Each RT Profile is counted as one (1) RT Profile, regardless of whether it is a Known RT Profile (has Personally Identifiable Information) or an Unknown RT Profile (no PII). The number of RT Profiles calculated for a given month will be the 4th highest number of RT Profiles held in all Production Instances counted on a daily basis during the month. |
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Personalization Calls |
A Personalization Call is a call to the Personalization API which, using a Real Time (RT) user identifier, returns a payload of up to 20 RT Attributes and Core ICDP attributes which are stored in the RT Decision Engine. The number of Personalization Calls for a given month will be the total number of Personalization Calls recorded in the RT Decision Engine(s) in all Production Instances for that month. |
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Incoming Events |
An Incoming Event is an incoming streaming event that is ingested into the Real Time (RT) Decision Engine. The number of Incoming Events is the total number of Incoming Events recorded in the RT Decision Engine(s) in all Production Instances for a given month. |
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Trigger Activations |
A Trigger Activation is an outgoing streaming event that is generated by the Real Time (RT) Decision Engine, which can result in a call to downstream streaming connections for an action to be taken. The number of Trigger Activations is the total number of outgoing events recorded in the RT Decision Engine(s) in all Production Instances for a given month. |
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Messages |
Messages measures the number of messages sent by a customer using Engage Studio in all Production Instances within a given month. Message types include, but are not limited to, emails and push notifications. |
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Predictions |
Predictions are generated as a result of training and prediction runs of Profiles through a machine learning model. The models include but are not limited to Next Best Product (NBP), Next Best Action (NBA), Recency-Frequency-Monetary (RFM), and Customer Lifetime Value (CLTV). The number of Predictions are recorded as the number of outputs from a prediction run for all Production Instances for a given month. |
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AutoML Tier 1/2/3 |
Automates machine learning (ML) process steps such as data processing, feature engineering, model selection and hyper-parameter tuning to reduce time to deploy ML models. Treasure AutoML provides users access to the AutoML capabilities from Treasure Workflows. AutoML is available in the following options: AutoML Tier1: AutoML Tier2: AutoML Tier3: |