AI Extract Detail
The Extract Detail stage enables workflows to intelligently analyze and extract structured data—such as text, number, decimal, Boolean, or date—from unstructured or semi-structured sources like previous output variables. It helps capture essential data points, key facts, and critical information, storing them in variables that can be reused in later stages of the workflow for efficient processing and automation.
AI Extract Detail
Select variable or fields:
The dropdown displays all variable names from previous stages.
If no variables are available from previous stages, it shows 'No variables found’.
Choose the input variable from which you want to extract data (e.g. Variable:Candidate_Summary)
This is the source text that the AI will analyze and extract.
Add Fields to Extract
Click on ➕ Add Option to define what information you want to extract. For each field:
a. Name
Provide a label for the field to extract (e.g., Candidate Name, Total Experience, Joining Date, Is Available, Location).
b. Select Data Type
Choose one of the following data types:
String – for names, titles, general text
Number – for integers like years of experience
Decimal – for values like salaries, ratings
Boolean – for true/false type answers (e.g., “Is the candidate available immediately?”)
Date – for values like DOB, application date
c. Add Instruction
Describe clearly what to extract from the input.
Examples:
Extract the full name of the applicant.
Extract total years of experience.
Extract the offered salary as a decimal value.
Extract whether the candidate is currently available (Yes/No).
Extract the date when the candidate can join.
Example Setup
Name
Data Type
Instruction
Full Name
String
Extract the full name of the candidate.
Experience
Number
Extract total years of experience.
Salary Expected
Decimal
Extract expected salary in INR.
Immediate Join
Boolean
Is the candidate available immediately?
DOB
Date
Extract date of birth of the candidate.
Output store:
In the Extract Detail stage, the output is stored in record or records data type variables,
If your Extract Detail stage allows you to define multiple fields (e.g., Name, Email, Experience), and these are returned as part of a single structured object (like a record), then yes — the output is effectively of record type.
If the stage processes a list of inputs (e.g., resumes), and extracts details from each, then it could produce an array of records → records type.
Use Case Examples
Resume Screening
Extract: Name, Experience, Skills, Current Location, Expected Salary
Support Ticket Triage
Extract: Issue Type, Product, Date of Issue, Urgency Level
Sales Lead Capture
Extract: Lead Name, Company, Email, Budget, Interested Service
AI Extract-Detail Under For Each Stage
When used inside a For Each stage, the Extract Detail stage helps process each item in a list (e.g., resumes or form responses) by extracting structured data—such as text, number, decimal, boolean, or date—from each item individually.
This is especially useful when handling bulk records or looping through repository entries or array variables.
How It Works
The For Each stage loops over a list of items (records or array).
For each item, the Extract Detail stage analyzes the selected input variable or fields (typically a field from the current record in the loop).
It extracts defined data points and stores them in variables for further actions like filtering, scoring, or storing in another repository.
Configuration Steps
1. For Each Setup
Repository selected: e.g., Candidate Tracker
Set condition: Highest Education is equal to BE
2. Extract Detail Configuration Inside For Each
a. Select Variable or Fields
The dropdown list displays the Variable and Repository fields selected in the 'For Each' stage.
Choose the input variable or fields that contains the data you want to analyze per item.
b. Add Fields to Extract
Click on ➕ Add Option to configure the fields to extract for each item in the loop.
Parameter
Description
Name
Name for the extracted field (e.g., Candidate Name, Experience)
Data Type
Select from: String, Number, Decimal, Boolean, or Date
Instruction
Give a clear instruction to the AI on what to extract from the input text
These extracted values are scoped per loop iteration and can be used for filtering, scoring, or record creation.
Example Use Case: Resume Screening Workflow
Scenario:
You have a Candidate Tracker repository with a field Resume Attachment. You want to extract candidate details like name, experience, and skills from each resume.
Configuration:
For Each: Repository = Candidate Tracker
Extract Detail Input: Resume
Fields to Extract:
Name
Data Type
Instruction
Full Name
String
Extract the full name of the candidate.
Experience
Number
Extract total years of experience.
Skills
String
Extract the list of key skills.
Notice Period
Number
Extract notice period in days.
Is Immediate Join
Boolean
Is the candidate available to join now?
Output Handling
Output from each Extract Detail execution is stored as record and records type variables.
These variables can be:
Used immediately in the next stage (e.g., conditional check, scoring)
Mapped into a new record (e.g., Add Record in another repository like “Screened Candidates”)
Extract Detail Under Condition Stage
When used under a Condition stage, the Extract Detail stage allows your workflow to first evaluate a condition and only extract data if the condition is met. This ensures that AI-powered extraction only runs when needed—e.g., when a specific input type or scenario is detected.
Select variable or fields:
The dropdown displays all variable names from previous stages.
If no variables are available from previous stages, it shows 'No variables found’.
Choose the input variable from which you want to extract data (e.g. Variable:Candidate_Profile)
This is the source text that the AI will analyze and extract.
Typical Use Case
Let’s say you receive multiple types of user inputs (e.g., complaint emails, sales inquiries, or resumes), and you want to extract details only if the intent is a “Job Application” or “Support Ticket”. You first evaluate the intent using an AI Option or Identify Intent, then conditionally run Extract Detail based on the result.
How It Works
Condition Stage: Evaluates a rule or AI-generated classification.
If Branch (True): Extract Detail runs only if the condition matches.
Else Branch (Optional): Can run a different flow or skip extraction.
Configuration Steps
1. Set Up the Condition Stage
Define a logical or AI condition to evaluate.
Example: Variable:Intent equals "Job Application"
2. Add Extract Detail in the IF Branch
Under the "Yes" branch of the Condition:
a. Select Variable or Fields
Choose the source variable (eg. Variable:Candidate_Summary)
b. Add Fields to Extract
Click ➕ Add Option for each data point you want to extract.
Parameter
Description
Name
Label for extracted value (e.g., Candidate Name, Skills)
Data Type
Choose from: String, Number, Decimal, Boolean, or Date
Instruction
Describe what to extract (e.g., Extract the applicant’s full name)
Example: Extract Only If Intent is Job Application
Condition Stage:
Condition: Variable:Intent is equal to Job Application
IF Branch:
Extract Detail Input: Resume
Fields to Extract:
Name
Type
Instruction
Full Name
String
Extract the full name of the applicant.
Experience
Number
Extract total years of experience.
Skills
String
Extract key skills.
Is Available
Boolean
Is the candidate available immediately?
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