📒Kaiya Learnings

Teach Kaiya how to interpret specific words and phrases

You can teach Kaiya Search how to interpret specific words or phrases in your search queries, so you get consistent, correct answers without re-phrasing. This enhances the search experience by ensuring that Kaiya understands and processes queries according to your specific business context.

• Phrase Learnings → fix the meaning of a word/short phrase (alias to a measure/dimension/filter).

• Query Learnings → lock down the entire question pattern (aggregation, grouping, filters, time windows, ranking) using a required Intent so Kaiya handles a pattern the same way every time.

When to use Phrase vs Query Learnings?

Phrase Learnings

• Ideal for aliases/synonyms and simple flags—map a single token to a measure/dimension/filter (e.g., supplier → Commercial Vendor Name)

• Suitable for personal shortcuts scoped to a user/BV (e.g., my region → Region IN {NE, Mid-Atlantic}), where meanings shouldn’t affect others.

• Ideal for cases where fixing one word/short phrase resolves ambiguity.

Query Learnings

• Ideal for multi-clause patterns that must behave identically across phrasings: time comparisons (MoM, Q3 vs Q2), per-group Top-N, vs plan/forecast, or thresholds + grouping.

• Suitable for org-standard questions where you require Intent to fix aggregation, grouping, filters, time logic, and ranking.

• Avoids repeated back-and-forth clarifications—capture the full pattern once (e.g., “top 3 customers per region by revenue”).

• Controls the output shape (ranked lists, variance tables, contributor breakdowns) when ambiguity spans beyond a single token.

With continuous learning:

• Users (or admins) can save corrections from a Kaiya session as new Learnings.

• When a new Learning overlaps an existing one, Kaiya warns and lets you merge or override.

Levels of Learnings

There are two levels of Kaiya Learnings:

• Business View-level Learning

• System-level Learning

Business View-level Learning

These are specific to the current Business View and do not affect other parts of the system. They are ideal for context-specific mappings, like associating "core customer reach" with the average profit within that particular Business View.

System-level Learning

These learnings are applied globally, affecting all users and queries on the platform, regardless of the Business View. They are suitable for establishing general rules and definitions, such as mapping abbreviations to their full meanings (e.g., PLV meaning Pluvicto).

Scope of Learnings

You can scope a Learning by owner and Business View (BV). The following takes the precedence of highest → lowest.

User-specific

• User + Business View — visible only to that user, only in the selected BV.

• User + All BVs — visible only to that user, across all BVs.

System-specific (admin only)

• System + BV — visible to all users, only in the selected BV.

• System + All BVs — visible to all users, across all BVs.

A Learning has two axes: Owner and Business View (BV) scope. If two Learnings cover the same phrase/query, the higher-precedence one is used.

Example:

• User creates Phrase Learning: “my region” → Region IN {NE, Mid-Atlantic} in Revenue_BV.

• Admin already has “my region” → Region IN {All East} (System + All BVs).

• In Revenue_BV for that user, the User + BV definition wins.