Prompts

This module is for creating and managing Prompts. They pair parameters into wholes that are then used for processing audio (transcriptions) and text inputs.

Configuration

Prompt — Essential configuration

On-screen elements:

• Essential:

  • Details:

    • Name: input field of the prompt. The saved name is automatically normalized to lowercase snake_case.

    • Language: dropdown field for processing the prompt

    • Prompt state: radio buttons for choosing Enabled, Disabled for all (completely disabled), or Disabled for rerun (disabled only for reruns)

    • Multi-chunk behavior: radio buttons for choosing which parts of a long, multi-chunk record the prompt processes:

      • Each (default): processes every chunk. Use it when the analysis should cover the complete input, for example sentiment or topics across the whole conversation or document. The partial outputs are consolidated into one result according to the selected parameters' Multi prompt behaviour.

      • First: processes only the opening chunk. Use it for information expected near the beginning, for example a greeting, introduction, or initial reason for contact.

      • Last: processes only the final chunk. Use it for information expected near the end, for example a farewell, closing statement, or final outcome.

Why the Multi-chunk behavior setting exists

Language models have limited context windows, so very long audio or text inputs may need to be broken into several chunks before processing. This prevents the end of a large document or recording transcript from being truncated.

Chunking is applied when the processed input exceeds 110,000 characters. There is no fixed recording-duration or word-count threshold:

• For Audio projects, it depends on the length of the generated transcript and its formatting, not directly on the recording duration.

• For Text/Email projects, it depends on the length and formatting of the processed text.

When an input contains multiple chunks, Multi-chunk behavior lets you decide whether the prompt processes every chunk, only the opening chunk, or only the final chunk. When Each is selected, the partial outputs are consolidated into a unified result according to the parameters' Multi prompt behaviour.

• Parameters:

  • Predefined parameter group: input field for selecting already predefined hardcoded parameter groups. Once any of them is selected, its predefined, hardcoded parameters are then listed in the Parameters field below.

  • Parameters: input field for selection of parameters (custom-made or predefined)

Predefined groups and parameters come from the deployed configuration and are listed directly in the interface. Their availability can vary between environments and versions.

Predefined (hardcoded) parameter examples and their descriptions

The entries below are examples from a previously documented configuration. Available predefined parameters can vary between environments and versions; use the parameters listed in the current interface as the authoritative source.

addressing	Value YES if the Agent used the Client’s first name or last name in the conversation. Value NO otherwise.		YES, NO	string	NO	WEIGHTED_VALUE
benefit	Did the agent mention the product benefit?		YES, NO	string	N/A	FIRST
call_script_summarization	Agent summarized Client's request to check if he understood correctly		NO, YES	string	NOT_FOUND	WEIGHTED_VALUE
call_script_telco_offering_accepted	Client accepted mobile phone service, package or tariff that Agent offered to him			string	NOT_FOUND	WEIGHTED_VALUE
call_script_telco_offering_value	Name of the offering, service, package or tariff that Agent offered to Client to buy, add or activate			string	NOT_FOUND	LAST
category	Most dominant topic Client wants to discuss			string	NOT_FOUND	FREQUENT
category_product	categorize a product of selling		insurance, savings, loans, investment, credit card	string	other	FIRST
client_behaviour_goodbye	Client's goodbye	Value YES if client said goodbye, else value NO	NO, YES	string	NOT_FOUND	LAST
client_behaviour_thanks	Client's client_behaviour_thanks	Value YES if client thanked for help, else value NO	NO, YES	string	NOT_FOUND	LAST
cross_sell	Value YES, if the Agent tried to sell more than just 1 product, or tried to cross sell, upsell another product. Value NO otherwise.		YES, NO	string	NO	FIRST
empathetic	Value YES if the Advisor responds empathetically to the Clients concerns and questions. Value NO otherwise.			string		FIRST
extract_client_customer_contract_number	Client's customer number or customer contract number			string	NOT_FOUND	FIRST
extract_client_email	Client's email			string	NOT_FOUND	FIRST
extract_client_first_name	Client's first name			string	NOT_FOUND	FIRST
extract_client_insurance_number	Client's insurance number			string	NOT_FOUND	FIRST
extract_client_last_name	Client's surname			string	NOT_FOUND	FIRST
extract_client_phone_number	Client's phone number			string	NOT_FOUND	FIRST
extract_client_service_number	Client's service number			string	NOT_FOUND	FIRST
farewell	Value YES if the Agent said goodbye or wished the Client a nice day. Value NO otherwise.		YES, NO	string	NO	WEIGHTED_VALUE
future_interest	Value YES if the Client has expressed interest in a certain banking product in a certain time frame, such as another day, later, another time, sometimes in a few weeks, months, in half a year etc. Value NO if the Client has no interest in any banking product at all and when client does not mention interest then value No interest mentioned		another day, later, another time, sometimes in a few weeks, months, in half a year, No interest	string	No interest mentioned	FIRST
future_interest_ii	Value YES if the Client has expressed interest in a certain banking product in a certain time frame, such as another day, later, another time, sometimes in a few weeks, months, in half a year etc. Value NO if the Client has no interest in any banking product at all and when client does not mention interest then value No interest mentioned		YES, NO	string	NO	FIRST
gathered_category	Choose category that fit this conversation the most			string	NOT_FOUND	FIRST
greeted	The value YES, if the agent greeted, introduced himself, said the name of the company. The value NO otherwise.		YES, NO	string	NO	FIRST
greeted_end_of_the_call	Yes , if agent greeted at the end of the call, otherwise NO		YES, NO	string	NO	FIRST
handle_it	How well did the agent handle these objections? categorize it			string		FIRST
handle_objections	Value YES if the Agent is able to handle Customers objections well. NO otherwise.		YES, NO	string	NO	FIRST
identification	Value YES if the Client’s first name, last name and date of birth were mentioned in the conversation. Value NO otherwise.		YES, NO	string	NO	WEIGHTED_VALUE
ideology_ukraine	True if message supports Ukraine or is againts Russia. False if message supports Russia or is againts Ukraine. Neutral if message is neutral about this topic.		False, True, Neutral	string	Neutral	WEIGHTED_VALUE
interest	rate the clients interest about product and categorize it		High, Moderate, Low	string	No interest	FIRST
interested_when	When will the Client be interested in the selected banking product? Return exactly one of the following options that is closest to what the Client said: Days, Week, 2 weeks, A few weeks, 3 weeks, Month, A few months, 2 months, 6 months, Year.		Days, Week, 2 weeks, A few weeks, 3 weeks, Month, A few months, 2 months, 6 months, Year, Tomorrow	string	Not mentioned	FIRST
introduction	Value YES if the Agent introduced themselves with their first name, last name, and company name. Value NO otherwise.		YES, NO	string	NO	FIRST
mifid_financial_products	Financial products that where mentioned or discussed in this Conversation by Agent of Client	string with values separated by comma		string	NOT_FOUND	CONCATENATE
mifid_financial_products_explained	If Agent explained risks or details about discussed financial products		False, True	string	FALSE	WEIGHTED_VALUE
mifid_relevant	True if conversation included any information that needs to be Mifid II regulated		False, True	string	FALSE	WEIGHTED_VALUE
obscene	All profanity, obscene words that are in the transcript. NOT_FOUND if none occur.			string		FIRST
other_help	Value YES if the Agent asked the Client whether they had any other requests or if there was any other way they could help. Value NO otherwise.		YES, NO	string	NO	WEIGHTED_VALUE
personalizing_offer	Value YES if the Agent tried to personalizing the offer to Clients needs/situation, rather then just presenting product as on a leaflet. Value NO otherwise.		NO, YES	string	NO	FIRST
react_to_offer	How did the customer react to the offer? categorize it		Positive, Interest, Disinterested, Disappointed, Polite, Neutral	string	Not mentioned	FIRST
recapitulation	Value YES if the Agent summarized the conversation and verified the contact details with the customer. Value NO otherwise.		YES, NO	string	NO	WEIGHTED_VALUE
rejection	List the main reason why the client does not want to purchase the product or service, why they are not interested.		Price Objection, Lack of Need, Competitor Preference, Budget Constraints, Lack of Understanding, Not the right time	string	Not mentioned	FIRST
rejection_reason_description	Summarize the main reason why the client does not want to purchase the product or service, why they are not interested.			string		FIRST
selling	Did the agents sell the product?		YES, NO	string	N/A	FIRST
sentiment_agent	Agent's sentiment at start of conversation		Helpful, Friendly, Unfriendly, Aggresive, Neutral, Other	string	Neutral	FREQUENT
sentiment_client_end	Client's sentiment at end of conversation		Relief, Gratitude, Frustration, Confusion, Anger, Neutral, Other	string	Neutral	LAST
sentiment_client_start	Client's sentiment at start of conversation		Relief, Gratitude, Frustration, Confusion, Anger, Neutral, Other	string	Neutral	FIRST
subcategory	Subcategory to the most dominant topic Client wants to discuss			string	NOT_FOUND	FREQUENT
subsubcategory	Subcategory to the most dominant topic Client wants to discuss			string	NOT_FOUND	FREQUENT
suggest_category	Most dominant topic Client wants to discuss			string	NOT_FOUND	FREQUENT
suggest_subcategory	Subcategory to the most dominant topic Client wants to discuss			string	NOT_FOUND	FREQUENT
summary	Summary of what was Conversation about	Maximum 20 words		string	NOT_FOUND	CONCATENATE
summary_long	Summary of what was Conversation about	Maximum 40 words		string	NOT_FOUND	CONCATENATE
summary_short	Summary of what was Conversation about	Maximum 10 words		string	NOT_FOUND	CONCATENATE
topic_dominant	Most dominant topic this Conversation was about			string	NOT_FOUND	FREQUENT
topic_first	First topic Client wants to discuss			string	NOT_FOUND	FIRST
topic_nondominant	Second most dominant topic this Conversation was about			string	NOT_FOUND	FREQUENT

• Previous parameter: input field for selecting a result from an earlier prompt and using it as input for the current prompt. Example: summary of the audio record (prompt_summary)

You can select parameter results from prompts that run earlier. The available name uses the format <prompt>_<parameter>.

Prompt — Advanced configuration

• Advanced:

  • Analysis enhancement:

    • LLM Instructions: input field for additional prompt specifics. E.g., output file type, processing specifics, structure requirement, etc. It is mainly used in some specific cases to fine-tune the output.

  • Conditions: use conditions to run a prompt only when selected values match the configured pattern.

    • Condition operator: choose how multiple conditions are combined.

      • AND: all conditions must match.

      • OR: at least one condition must match.

      • The default is AND.

    • Add new condition: adds another condition.

      • Parameter: enter the exact, case-sensitive name of a value available to the prompt.

        • Analytical parameter results from earlier prompts use the available <prompt>_<parameter> name.

        • Metadata values normally use an available meta_input_<metadata_name> name.

        • A parameter name is not a regex or a path into nested metadata. A dot does not select a value inside a nested object.

          • Example: meta_input_campaign_metadata.campaing_type

      • Value: enter basic text or a regular expression (regex) to match the selected parameter. Enter a regex directly, without / characters around it.

        • Basic text matching (default): travel_energy matches any existing value that contains travel_energy.

        • Exact matching: ^travel_energy$ matches only when the complete value is travel_energy.

        • Case-insensitive exact matching: (?i)^travel_energy$ matches only travel_energy, regardless of letter case.

        • Example — use nested metadata:

          • Suppose the source metadata contains:

            {
              "campaign_metadata": {
                "campaing_type": "travel_energy"
              }
            }

          • The desired nested field, meta_input_campaign_metadata.campaing_type, is not available as a separate Parameter unless the source metadata was already flattened into a field with that exact name.

          1. In Parameter, enter meta_input_campaign_metadata.

          2. In Value, use one of these patterns:

             • travel_energy to match this value anywhere in the nested metadata.

             • ['"]campaing_type['"]\s*:\s*['"]travel_energy['"] to match the specific campaing_type field with the value travel_energy.

          3. The prompt runs only when the selected pattern matches.

        • Important:

          • A blank Parameter makes that condition pass. With OR, one blank condition can make the complete condition group pass.

          • A blank Value matches every existing value. A missing parameter or a parameter with no value does not match.

          • Escape regex characters such as ., *, +, ?, (, ) and [ when they should be treated as ordinary characters.

          • An invalid regex can cause a processing error. Test patterns before using them in a live workflow.

          • Matching nested metadata is less reliable than using a flattened field. Where possible, use a dedicated field such as meta_input_campaign_type.

  • Custom provider: toggle for turning a custom provider on or off. When it is on, configure the provider settings below.

    • Provider: dropdown menu with options representing LLM providers (Azure OpenAI, Anthropic, Gemini, Groq, or OpenAI)

    • API Key: input field

    • Model name: input field

    • API base: input field for entering a URL

    • API version: input field

    • Reasoning effort: dropdown with none, minimal, low, medium, high, and xhigh.

• Create: button for creating the prompt with the latest configuration. Name and at least one Parameter are required.

• Delete: button for deleting the prompt. It appears alongside Save when editing an existing prompt.

Tip: Use the predefined parameters for inspiration, but add little details for your individual use-case. (i.e., the exact call script for your agents to introduce to customers, like: The value YES, if the agent greeted, introduced himself and asked "How can I help you?". The value NO otherwise.

vs. the default:

The value YES, if the agent greeted, introduced himself, said the name of the company. The value NO otherwise.

Management

• The order of prompts defines their running order. Drag prompts to reorder them, then select Save.

On-screen elements:

• Upper part:

  • Search prompts: bar for searching parameters based on their name

  • + Create: button for creating a new prompt

  • Select: enters bulk selection mode

    • Select all: selects every prompt in the current list

    • Done: exits bulk selection mode

    • Prompt state: dropdown field for changing the state to one of these: Enabled, Disabled for all (completely disabled), or Disabled for rerun (disabled only for reruns)

    • Delete: button for deleting the selected prompt(s)

• List of prompts: (Elements are listed from the left)

  • Name: of the prompt

  • Pencil: icon button for editing the prompt

  • Command line: icon indicating the prompt state

  • Language: used for processing the prompt

  • Prompt provider type: displaying Default provider or the configured custom provider

  • Parameters preview: displaying a preview of the parameters used by the prompt, upon hovering over them, their definition is displayed

• Floating buttons:

  • Export: for exporting all prompts in a JSON-formatted file

  • Import: for importing prompts in a JSON-formatted file

  • Save: for saving prompt changes