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Schema-Level Prompting

subqueries support

Feature Description

Lumenore introduces Schema-Level Prompting, allowing you to create prompts in conversational language to define how the AI should behave when processing data. For example, users can specify instructions like, "When I mention 'yearly sales', take data from the order date year column of my schema," or "When I say gain, always use profit column"  These prompts can include detailed instructions about goals, constraints, and data interpretations, ensuring that the AI processes data according to the user's specific requirements. Once a schema-level prompt is defined, it is easily integrated into the system prompt of the AI modules, ensuring the AI operates with the customized context provided by the user. 

End User Business Benefits

no code

Higher Accuracy

Reduces misinterpretation of business terms.

Faster decision

Consistency

Ensures everyone sees data through the same definitions.

efficiency increase

Time Savings

Cuts down on rework and clarifications.

error-reduction

Customization

Lets teams align insights with their own KPIs and logic.

time saving

Flexibility

Adaptable to different industries and use cases.

time saving

User Control:

Empowers business users to guide AI without technical skills.

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  • Healthcare

    • Define admissions so it always refers to the patient admission records. 
    • Standardize treatment cost to always come from procedure-related expenses. 
    • Ensure readmission rate queries are consistently tied to discharge and re-admission records.

  • Manufacturing 

    • Map downtime so it always pulls from machine inactivity records. 
    • Standardize yield to consistently reflect usable units produced. 
    • Define supplier reliability to be based on delivery timeliness and defect records.

  • Retail & E-commerce

    • Link yearly sales to sales records from the order year. 
    • Standardize returns to always include return reasons and quantities. 
    • Ensure profit margin queries consistently reflect the right financial data points.

  • Banking & Financial Services

    • Define net gain so it always reflects the correct income and expense values.
    • Standardize delinquency rate queries to consistently pull from overdue loan records.
    • Map assets under management to customer portfolio value.

  • Government & Public Sector

    • Standardize employment rate so it refers to employed citizens within the working population.
    • Define citizen service requests to always include complaint type and resolution status.
    • Ensure budget utilization refers to actual versus allocated government spending.

  • Contact Centers / Customer Experience 

    • Map average handling time to the complete call duration records.
    • Define customer satisfaction to always use survey feedback scores.
    • Standardize first call resolution to consistently reflect resolved issues in the first interaction.

application areas