Skip to main content
When building automated workflows, structure matters. Any response you generate, especially from AI models, needs to follow a predictable format so it can be:
  • Referenced by later steps
  • Used in conditions or classifications
  • Pushed reliably to CRMs, grids, or integrations
AI models are powerful, but by default they can:
  • Change response formats
  • Add extra text
  • Reorder information
  • Hallucinate structure even with strict prompts
To solve this, Bitscale provides Output Formatting, a built-in way to enforce structured AI responses across all AI enrichments.

​
Why Output Formatting Is Important

Without structured outputs:
  • Workflows break unpredictably
  • Downstream enrichments fail
  • CRM pushes become unreliable
  • Automation becomes fragile
With output formatting:
  • Every run produces the same schema
  • Columns are always consistent
  • AI results can safely drive logic and actions

​
Where Output Formatting Is Available

Output formatting is available on:
  • Bit Agent
  • GPT / Claude / AI enrichments
  • Any text-based AI step
You’ll find it under Set Output Format in the enrichment configuration.

​
Fields vs Lists

Bitscale supports two output types:

​
Fields

  • Used for single values or comma-separated values
  • Best for:
    • Industry
    • ICP classification
    • Boolean flags
    • Short summaries
Example: 
Industry: SaaS, DevTools
Target Demography: Mid-market B2B

​
Lists

  • Used for multiple structured entries
  • Each item is treated as a separate entity
  • Best for:
    • Event attendees
    • Customers
    • Technologies
    • People lists
    • Anything you may want to explode into rows later
Example: 
Customer 1: Name, Company
Customer 2: Name, Company
If you plan to export or explode results into another grid, always use Lists.

​
Manually Defining Output Formats

You can manually define:
  • Field name
  • Data type (text, boolean, number, etc.)
  • Output structure
This gives maximum control but requires clarity on what the model should return.
For most users, the easiest and safest approach is Use AI.

​
How it works

  • Bitscale reads your prompt
  • Understands the intent
  • Automatically generates the correct output schema

​
Example

Prompt:
Go through @company_website and find their target demography and customers
Click Use AI, and Bitscale generates:
  • Target Demography
  • Industry
  • Customers
All correctly typed and structured. This dramatically reduces prompt engineering effort and prevents format drift.

​
Running and Storing Structured Outputs

Once the enrichment runs:
  1. The AI response is forced into the defined structure
  2. Each output field becomes a reusable column
  3. These columns can now be:
    • Referenced in later prompts
    • Used in run conditions
    • Exported to CRMs
    • Passed to other grids or integrations
No matter how many times the enrichment runs, the structure remains consistent.

​
Best Practices

  • Always use output formatting for AI-driven workflows
  • Use Fields unless you explicitly need row-level expansion
  • Prefer Use AI unless you have very strict schema requirements
  • Treat structured outputs as foundational workflow primitives