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@pasar6987/sf-core-ai-einstein
Machine learning models, AI insights, discovery predictions, natural language processing, recommendation engines, and generative AI capabilities powered by Salesforce Einstein.
Native (downloadable) · Latest 1.0.1 published Mar 4, 2026 · 48 datasets / 25 measures in the latest preview · Updated Mar 11, 2026
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@pasar6987/sf-core-ai-einstein
Machine learning models, AI insights, discovery predictions, natural language processing, recommendation engines, and generative AI capabilities powered by Salesforce Einstein.
Overview
| Count | |
|---|---|
| Objects (Datasets) | 48 |
| Dimensions | 612 |
| Measures | 25 |
| Relationships | 24 |
Objects
- AIInsightAction — Represents an Einstein prediction insight action.
- AIInsightFeedback — Represents an Einstein prediction insight feedback.
- AIInsightReason — Represents an Einstein prediction insight reason.
- AIInsightValue — Represents an Einstein prediction insight value.
- AIMetric — AI Live Model Metrics - AIMetric
- AIRecordInsight — Represents an Einstein prediction insight.
- AIResearchPromptResult — Represents the research result generated by Einstein from a prompt template.
- AiExternalModelReference — AI External Model References - AiExternalModelReference
- AiGenActionItem — Represents business actions suggested by generative AI. AI-generated action items are sent to either agents for automatic execution or human users for review, depending on org preference and if there are any errors in the process.
- AiJobRun — Represents an execution instance of an AI job. This object tracks the overall status and manages the lifecycle of the job from initiation to completion.
- AiJobRunItem — Stores an individual item associated with a parent AiJobRun, including the inputs and resulting response.
- AiModelLanguage — An object that stores language related information that is generated for each AI model.
- DiscoveryAIModel — Discovery AI Models - DiscoveryAIModel
- DiscoveryDeployedModel — Discovery Deployed Models - DiscoveryDeployedModel
- DiscoveryDplyMdlCstmzField — Discovery Deployed Model Customizable Fields - DiscoveryDplyMdlCstmzField
- DiscoveryFieldMap — Discovery Field Maps - DiscoveryFieldMap
- DiscoveryFilter — Discovery Filters - DiscoveryFilter
- DiscoveryFilterValue — Discovery Filter Values - DiscoveryFilterValue
- DiscoveryGoal — Discovery Goals - DiscoveryGoal
- DiscoveryModelField — Discovery Model Fields - DiscoveryModelField
- DiscoveryRecipient — Discovery Recipients - DiscoveryRecipient
- DiscoveryRefreshConfig — Discovery Refresh Configs - DiscoveryRefreshConfig
- DiscoveryRefreshJob — Discovery Refresh Jobs - DiscoveryRefreshJob
- DiscoveryRefreshTask — Discovery Refresh Tasks - DiscoveryRefreshTask
- DiscoveryScoringJob — Discovery Scoring Jobs - DiscoveryScoringJob
- DiscoveryScoringJobItem — Discovery Scoring Job Items - DiscoveryScoringJobItem
- DiscvDplyMdlCstmzFieldTxt — Discovery Deployed Model Customizable Field Text - DiscvDplyMdlCstmzFieldTxt
- EinsteinAnswerFeedback — Einstein Answer Feedback - EinsteinAnswerFeedback
- GenAIConversationSummary — Represents a generated summary of a voice or video call.
- GenAiPlannerFunctionDef — Represents a relationship between the agent planner service and agent actions.
- GenAiPluginDefinition — Represents an agent topic, which is a category of actions related to a particular job to be done by AI agents.
- MLFilterValue — ML Filter Values - MLFilterValue
- MLModel — Represents an AI model that can be used in Einstein Prediction Builder, Einstein Recommendation Builder, and other Einstein features.
- MLModelFactor — Represents a field value that has a positive or negative effect on the model’s score.
- MLModelFactorComponent — Represents information about the related MLModelFactor. For example, this object can represent a field value or a field range such as “Title = CEO” or “Annual Revenue >10000000”.
- MLModelMetric — Represents a metric or statistic about the related model, such as accuracy, precision, or RSquared. Use a model’s metrics to learn about its performance and to compare it with other models.
- MLRecommendationDefinition — For internal use only.
- MlFeatureValueMetric — ML Feature Value Metrics - MlFeatureValueMetric
- MlIntentUtteranceSuggestion — Represents a customer input, used for training purposes in the feedback loop process of a conversation. Admins can add these inputs to the intent training model.
- ModelFactor — ModelFactors - ModelFactor
- NLPhrase — CQ Phrases - NLPhrase
- NLQueryFragment — CQ Fragments - NLQueryFragment
- Recommendation — Represents the recommendations surfaced as offers and actions for Einstein Next Best Action.
- RecommendationFeedback — Recommendation Feedback - RecommendationFeedback
- RecommendationResponse — Represents the user responses to a presented offer or recommendation for Einstein Next Best Action. This object is available in API version 51.0 and later.
- RecordRecommendation — Record Recommendations - RecordRecommendation
- ReplyAIRecommendation — Reply AI Recommendations - ReplyAIRecommendation
- TopInsight — For internal use only.
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Datasets 0 / Measures 0 / Dimensions 0 / Relationships 0
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