Processing Components

Processing components transform, combine, and manipulate data as it flows through your automation. Use them to prepare data for conditions, format content for actions, or extract specific values.

Data Object Fundamentals

All data in Agent Studio flows as Data objects - structured key-value containers:

{
  "account_name": "Acme Corp",
  "health_score": 75,
  "contacts": [
    { "name": "John", "role": "Champion" },
    { "name": "Jane", "role": "Executive Sponsor" }
  ]
}

Processing components modify these objects—adding fields, filtering keys, combining multiple objects, or extracting specific values.

Create Data V2

Creates a new Data object with specified key-value pairs.

When to Use

Initialize data at the start of a flow
Create structured data from multiple sources
Build payloads for API calls or actions

Configuration

Field	Description
Number of Fields	How many key-value pairs (1-15)
Field 1 Key	Name of the first field
Field 1 Value	Value (supports @ notation)
…	Additional fields as configured

Example: Build Email Context

Configuration:

Field 1 Key: recipient_name
Field 1 Value: @account_data.owner_name

Field 2 Key: account_name
Field 2 Value: @account_data.name

Field 3 Key: health_score
Field 3 Value: @account_data.health_score

Field 4 Key: alert_type
Field 4 Value: health_drop

Output:

{
  "recipient_name": "Jane Smith",
  "account_name": "Acme Corp",
  "health_score": 65,
  "alert_type": "health_drop"
}

Update Data V2

Adds or updates fields in an existing Data object.

When to Use

Add computed fields to existing data
Append metadata or timestamps
Modify values for downstream processing

Configuration

Field	Description
Number of Fields	How many fields to add/update
Field N Key	Field name to add or update
Field N Value	New value (supports @ notation)

Example: Add Timestamp and Flag

Input:

{
  "account_name": "Acme Corp",
  "health_score": 65
}

Configuration:

Field 1 Key: processed_at
Field 1 Value: (current timestamp)

Field 2 Key: requires_attention
Field 2 Value: true

Output:

{
  "account_name": "Acme Corp",
  "health_score": 65,
  "processed_at": "2024-02-20T10:30:00Z",
  "requires_attention": true
}

Filter Data V2

Creates a new Data object containing only specified keys.

When to Use

Remove sensitive fields before logging
Reduce data size for downstream processing
Extract specific fields from complex objects

Configuration

Field	Description
Keys	Comma-separated list of keys to keep

Example: Keep Only Essential Fields

Input:

{
  "account_id": "acc_123",
  "account_name": "Acme Corp",
  "owner_email": "jane@company.com",
  "internal_notes": "Sensitive info...",
  "api_key": "secret..."
}

Configuration:

Keys: account_id, account_name, owner_email

Output:

{
  "account_id": "acc_123",
  "account_name": "Acme Corp",
  "owner_email": "jane@company.com"
}

Extract Key V2

Extracts a single value from a Data object.

When to Use

Get a specific field for a condition
Extract a value to use as a standalone input
Access nested values

Configuration

Field	Description
Key	The key to extract (supports dot notation for nested values)

Example: Extract Nested Value

Input:

{
  "account": {
    "name": "Acme Corp",
    "primary_contact": {
      "email": "john@acme.com"
    }
  }
}

Configuration:

Key: account.primary_contact.email

Output:

{
  "value": "john@acme.com"
}

Combine Data V2

Merges multiple Data objects into one.

When to Use

Combine data from multiple sources
Merge results from parallel paths
Aggregate data for reporting

Configuration

Field	Description
Operation	How to combine: Concatenate, Append, Merge, or Join
Inputs	Connect multiple data inputs

Operations Explained

Concatenate

Combines arrays of Data objects into a single array.

Input 1: [{ "a": 1 }, { "a": 2 }]
Input 2: [{ "a": 3 }]
Output:  [{ "a": 1 }, { "a": 2 }, { "a": 3 }]

Append

Adds new Data objects to an existing array.

Input 1: [{ "a": 1 }]
Input 2: { "a": 2 }
Output:  [{ "a": 1 }, { "a": 2 }]

Merge

Combines fields from multiple objects into one (later values override earlier).

Input 1: { "a": 1, "b": 2 }
Input 2: { "b": 3, "c": 4 }
Output:  { "a": 1, "b": 3, "c": 4 }

Join

Combines objects based on a common key.

Input 1: { "id": 1, "name": "Acme" }
Input 2: { "id": 1, "score": 75 }
Join Key: id
Output:  { "id": 1, "name": "Acme", "score": 75 }

Select Data V2

Selects a single item from a list of Data objects by index.

When to Use

Get the first or last item from a list
Access a specific item by position
Extract one result from a query

Configuration

Field	Description
Index	Position to select (0-based, negative values count from end)

Example: Get First Account

Input:

[
  { "name": "Acme Corp", "score": 75 },
  { "name": "Beta Inc", "score": 82 },
  { "name": "Gamma LLC", "score": 60 }
]

Configuration:

Index: 0

Output:

{ "name": "Acme Corp", "score": 75 }

Example: Get Last Item

Configuration:

Index: -1

Output:

{ "name": "Gamma LLC", "score": 60 }

Calculate Expression V2

Evaluates mathematical expressions on data fields.

When to Use

Compute percentages or ratios
Perform arithmetic operations
Calculate derived metrics

Configuration

Field	Description
Expression	Mathematical expression (supports @ notation for values)
Output Key	Name for the result field

Supported Operations

Operation	Syntax	Example
Addition	`+`	`@a + @b`
Subtraction	`-`	`@total - @discount`
Multiplication	`*`	`@price * @quantity`
Division	`/`	`@score / 100`
Modulo	`%`	`@value % 10`
Parentheses	`()`	`(@a + @b) * @c`

Example: Calculate Percentage

Input:

{
  "current_score": 75,
  "max_score": 100
}

Configuration:

Expression: (@current_score / @max_score) * 100
Output Key: percentage

Output:

{
  "current_score": 75,
  "max_score": 100,
  "percentage": 75
}

Current Date V2

Returns the current date and time in a selected timezone.

When to Use

Get the current timestamp for data enrichment
Compare dates in conditions
Add timestamps to records or messages

Configuration

Field	Description
Timezone	Select the timezone (default: UTC). Supports all standard timezones.

Output Data

{
  "success": true,
  "timezone": "America/New_York",
  "datetime": "2024-02-20 10:30:00 EST",
  "date": "2024-02-20",
  "time": "10:30:00"
}

Date Formatter V2

Automatically formats all date fields found in a Data object to a specified format.

When to Use

Standardize date formats before sending emails or Slack messages
Convert ISO dates to human-readable formats
Prepare data for external API calls that require specific date formats

Configuration

Field	Description
Date Format	Target format for all date fields (e.g., `%Y-%m-%d`, `%B %d, %Y`)

How It Works

The component recursively scans all fields in the input Data object (including nested objects), detects ISO date strings, and reformats them to the specified format.

Example

Input:

{
  "account_name": "Acme Corp",
  "renewal_date": "2024-06-15T00:00:00Z",
  "last_activity": "2024-02-20T14:30:00Z"
}

Configuration:

Date Format: %B %d, %Y

Output:

{
  "account_name": "Acme Corp",
  "renewal_date": "June 15, 2024",
  "last_activity": "February 20, 2024"
}

Using @ Notation

The @ symbol references values from incoming data:

Syntax	Description	Example Result
`@field`	Top-level field	`@name` → “Acme”
`@field.nested`	Nested field	`@account.owner.name` → “Jane”
`@field[0]`	Array index	`@contacts[0]` → First contact
`@`	Entire data object	Full incoming data

Dynamic Field References

You can build field references dynamically:

Field Key: alert_@account_data.priority_level

If priority_level is “high”, creates field alert_high.

Common Patterns

Pattern: Data Enrichment Pipeline

Trigger → Create Base Data → Add Metadata → Add Computed Fields → Action

Pattern: Data Filtering Before Action

Trigger → Filter Sensitive Fields → Send to External API

Pattern: Aggregate Multiple Sources

┌─ SQL Query 1 ─┐
               ├──▶ Combine Data ──▶ Process
└─ SQL Query 2 ─┘

Pattern: Extract and Validate

Trigger → Extract Key → Condition (not empty) → Action

Fetch Object Data V2

Fetches the latest data for an entity from the database, returning a fresh Data object. This is useful when earlier components in the flow may have modified entity data (e.g., after a Sleep component or Human-in-the-Loop pause) and you need the most current values.

When to Use

After a Sleep V2 component, to get updated data that may have changed during the wait
After a Human-in-the-Loop pause, to pick up any manual changes
When you need to re-read entity data that another automation may have modified
To ensure downstream components work with the latest field values

Configuration

Field	Description
Entity Type	The type of entity to fetch (Account, Contact, Opportunity, etc.)
Entity ID	The ID of the entity to fetch (supports @ notation)

Output Data

Returns a Data object with all current fields for the entity, identical in structure to what the trigger segment provides.

Example: Refresh After Sleep

Trigger (Account) ──→ Sleep (24 hours) ──→ Fetch Object Data ──→ Check Health Score
                                              │
                                              └─ Returns fresh account data
                                                 including any changes made
                                                 during the 24-hour wait

Best Practices

Build data incrementally

Start with Create Data for essential fields, then use Update Data to add more as needed.

Filter before external calls

Remove sensitive or unnecessary fields before sending data to external systems.

Name output keys clearly

Use descriptive key names that indicate the data’s purpose and origin.

Handle missing keys

Use conditions to check if required keys exist before processing them.

Next Steps

Logic Components

Add conditional routing

Action Components

Use processed data in actions

​Processing Components

​Data Object Fundamentals

​Create Data V2

​When to Use

​Configuration

​Example: Build Email Context

​Update Data V2

​When to Use

​Configuration

​Example: Add Timestamp and Flag

​Filter Data V2

​When to Use

​Configuration

​Example: Keep Only Essential Fields

​Extract Key V2

​When to Use

​Configuration

​Example: Extract Nested Value

​Combine Data V2

​When to Use

​Configuration

​Operations Explained

​Concatenate

​Append

​Merge

​Join

​Select Data V2

​When to Use

​Configuration

​Example: Get First Account

​Example: Get Last Item

​Calculate Expression V2

​When to Use

​Configuration

​Supported Operations

​Example: Calculate Percentage

​Current Date V2

​When to Use

​Configuration

​Output Data

​Date Formatter V2

​When to Use

​Configuration

​How It Works

​Example

​Using @ Notation

​Dynamic Field References

​Common Patterns

​Pattern: Data Enrichment Pipeline

​Pattern: Data Filtering Before Action

​Pattern: Aggregate Multiple Sources

​Pattern: Extract and Validate

​Fetch Object Data V2

​When to Use

​Configuration

​Output Data

​Example: Refresh After Sleep

​Best Practices

​Next Steps

Logic Components

Action Components

Processing Components

Data Object Fundamentals

Create Data V2

When to Use

Configuration

Example: Build Email Context

Update Data V2

When to Use

Configuration

Example: Add Timestamp and Flag

Filter Data V2

When to Use

Configuration

Example: Keep Only Essential Fields

Extract Key V2

When to Use

Configuration

Example: Extract Nested Value

Combine Data V2

When to Use

Configuration

Operations Explained

Concatenate

Append

Merge

Join

Select Data V2

When to Use

Configuration

Example: Get First Account

Example: Get Last Item

Calculate Expression V2

When to Use

Configuration

Supported Operations

Example: Calculate Percentage

Current Date V2

When to Use

Configuration

Output Data

Date Formatter V2

When to Use

Configuration

How It Works

Example

Using @ Notation

Dynamic Field References

Common Patterns

Pattern: Data Enrichment Pipeline

Pattern: Data Filtering Before Action

Pattern: Aggregate Multiple Sources

Pattern: Extract and Validate

Fetch Object Data V2

When to Use

Configuration

Output Data

Example: Refresh After Sleep

Best Practices

Next Steps