Semantic extensions of Intelligence API enabling AI Agents

Building up semantic understanding of Celonis data in a specific business context (Knowledge Model - KM) so that third-party (3P) AI Agents can figure out the right way to query Celonis data. Therefore, Intelligence API is being enhanced to provide:

• Structure discovery : A new endpoint focusing on the KM data structures (including schema and description).
• Content discovery : A new endpoint providing statistical profiling of the data contents per KM record.
• Relationship discovery : To be added in the future. Future extensions will include the supply of the necessary process context to the 3P AI agents to power business process automation.

  3P AI Agent Enablement (BETA program) ¹

  Knowledge Model Semantic OpenAPI Spec

  To retrieve the semantic specification of a Knowledge Model - KM (according to Open API Initiative), either in json or yml format, you need to consume the endpoint: GET /knowledge-models/{{km-id}}/spec You have the option to select either all KM records (including the auto-generated) or only the curated ones by submitting the parameter curated=true. The Knowledge Model semantic metadata, including schema and data descriptions, are shared with the 3P agent enabling them to understand Celonis context and data.

  Knowledge Model Record Semantic Data Content Statistics

  To retrieve the Knowledge Model - KM record content statistics, you need to consume the endpoint: GET /knowledge-models/{{km-id}}/records/{{record-id}}/summary The results contain:

• The Schema array
• The Data Sample array
• The Shape array (number of rows, number of columns
• The Column Summary Statistics array including the following metrics for each KM record field (excluding KPIs, flags and augmented attributes):
  • count : Number of non-null values (applicable to all field types)
  • unique : Number of unique non-null values (applicable only to strings & timestamps)
  • top : Most frequent value (applicable only to strings & timestamps)
  • freq : Frequency of the most frequent value (applicable only to strings & timestamps)
  • mean : Mean of the values (applicable only to numeric fields)
  • std : Standard deviation of the values (applicable only to numeric fields)
  • min : Minimum value (applicable only to numeric fields)
  • max : Maximum value (applicable only to numeric fields)
  • 25% percentile (applicable only to numeric fields)
  • 50% percentile (applicable only to numeric fields)
  • 75% percentile (applicable only to numeric fields) The optional parameters controlling which data will be analyzed are:
• filters the filters to be applied on data contents (column statistic profiling may differ significantly depending on the applied filter); default none
• fields the fields whose contents will be analyzed (if omitted all record fields will be statistically profiled); default all
• excludeFields the fields to exclude from the statistical analysis; default none
• sampleSize for requesting a specific number of rows for the data; default 10

  Knowledge Model Semantic Query

  To query the Knowledge Model, you need to consume the endpoint: GET /knowledge-models/{{km-id}}/query. The parameters of /query are similar to /data endpoint with the difference that we have an optional parameter called kpis to retrieve the KPIs of the knowledge model. The response format is structured as a json object compared to the array of name and value, you can consult here /query endpoint.

  Knowledge Model Record Semantic Query

  To query the Knowledge Model - KM record data, you need to consume the endpoint: GET /knowledge-models/{{km-id}}/records/{{record-id}}/query The same parameters as the /data endpoint are supported with only difference that fields is optional. If omitted, all KM record fields are included. The response format is structured as a json object compared to the array of name, you have an example here /record/query.

  Fuzzy Search

  This feature fuzzy string search try to find the best match in a string. It is found in the following endpoints: /query, /record/query and /data.