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The schema parameter defines the structure of your response data. It must be a valid JSON Schema.

​
Basic Schemas

Basic company information in an array format.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "name": { "type": "string" },
      "domain": { "type": "string" },
      "description": { "type": "string" }
    }
  }
}
Example output:
[
  {
    "name": "Example Corp",
    "domain": "example.com",
    "description": "A technology company"
  }
]
Single company information as an object.
{
  "type": "object",
  "properties": {
    "name": { "type": "string" },
    "domain": { "type": "string" },
    "founded_year": { "type": "number" },
    "headquarters": { "type": "string" },
    "industry": { "type": "string" }
  }
}
Example output:
{
  "name": "Example Corp",
  "domain": "example.com",
  "founded_year": 2020,
  "headquarters": "San Francisco, CA",
  "industry": "Technology"
}

​
Contact Information

Company data enriched with CEO contact information.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company_name": { "type": "string" },
      "domain": { "type": "string" },
      "ceo_name": { "type": "string" },
      "ceo_email": { "type": "string", "format": "email" },
      "ceo_linkedin": { "type": "string", "format": "uri" },
      "ceo_phone": { "type": "string" }
    },
    "required": ["company_name", "domain"]
  }
}
Detailed contact information with multiple fields.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company": { "type": "string" },
      "contact_name": { "type": "string" },
      "title": { "type": "string" },
      "email": { "type": "string", "format": "email" },
      "phone": { "type": "string" },
      "linkedin": { "type": "string", "format": "uri" },
      "twitter": { "type": "string" }
    }
  }
}

​
Financial Data

Financial metrics and funding information.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company_name": { "type": "string" },
      "revenue": { "type": "string" },
      "employees": { "type": "number" },
      "funding_stage": { "type": "string" },
      "total_funding": { "type": "string" },
      "last_funding_date": { "type": "string" },
      "valuation": { "type": "string" }
    }
  }
}
Investor and funding round information.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company_name": { "type": "string" },
      "round_type": { "type": "string" },
      "amount_raised": { "type": "string" },
      "date": { "type": "string" },
      "lead_investor": { "type": "string" },
      "participating_investors": {
        "type": "array",
        "items": { "type": "string" }
      }
    }
  }
}

​
Industry-Specific

Schema optimized for SaaS company data.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company_name": { "type": "string" },
      "domain": { "type": "string" },
      "product_name": { "type": "string" },
      "product_category": { "type": "string" },
      "pricing_model": { "type": "string" },
      "target_market": { "type": "string" },
      "integrations": {
        "type": "array",
        "items": { "type": "string" }
      }
    }
  }
}
Schema for e-commerce and retail companies.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "brand_name": { "type": "string" },
      "website": { "type": "string" },
      "product_categories": {
        "type": "array",
        "items": { "type": "string" }
      },
      "marketplaces": {
        "type": "array",
        "items": { "type": "string" }
      },
      "annual_revenue": { "type": "string" },
      "headquarters": { "type": "string" }
    }
  }
}
Schema for healthcare and medical organizations.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "facility_name": { "type": "string" },
      "facility_type": { "type": "string" },
      "address": { "type": "string" },
      "specialties": {
        "type": "array",
        "items": { "type": "string" }
      },
      "bed_count": { "type": "number" },
      "accreditation": { "type": "string" }
    }
  }
}

​
Complex Structures

Complex nested structure with multiple levels.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company": {
        "type": "object",
        "properties": {
          "name": { "type": "string" },
          "domain": { "type": "string" },
          "description": { "type": "string" }
        }
      },
      "leadership": {
        "type": "object",
        "properties": {
          "ceo": { "type": "string" },
          "cto": { "type": "string" },
          "cfo": { "type": "string" }
        }
      },
      "metrics": {
        "type": "object",
        "properties": {
          "employees": { "type": "number" },
          "revenue": { "type": "string" },
          "growth_rate": { "type": "string" }
        }
      }
    }
  }
}
Schema with required and optional fields.
{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "company_name": { "type": "string" },
      "domain": { "type": "string" },
      "industry": { "type": "string" },
      "founded_year": { "type": "number" },
      "description": { "type": "string" }
    },
    "required": ["company_name", "domain"],
    "additionalProperties": false
  }
}
Fields listed in required must be present in the response. Optional fields may be omitted if data is unavailable.

​
Field Types Reference

  • String
  • Number
  • Boolean
  • Array
  • Object
Text data of any length.
{
  "field_name": { "type": "string" }
}
With format:
{
  "email": { "type": "string", "format": "email" },
  "url": { "type": "string", "format": "uri" },
  "date": { "type": "string", "format": "date" }
}

​
Best Practices

Be Specific

Define clear property names that match the data you’re requesting

Use Formats

Specify formats for emails, URLs, dates to ensure proper validation

Mark Required Fields

Use required array to specify which fields must be present

Keep It Simple

Start with simple schemas and add complexity as needed

​
Tips for Better Results

1

Match Query to Schema

Ensure your natural language query asks for the same fields defined in your schema
2

Use Descriptive Names

Use clear, descriptive property names like ceo_email instead of e
3

Test Incrementally

Start with a few fields and gradually add more to your schema
4

Review Responses

Check the raw field in responses to understand how the AI interpreted your query

​
Next Steps

Create Query

Use these schemas in your API queries

Quick Start

See complete examples with schemas
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