> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nrev.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Get Company Vendors

> Fetch and enrich your company data with vendor relationships, so you can map ecosystems, run intelligence, and enrich pipelines.

## What It Does

* Retrieves vendor relationships for a target company domain and outputs normalized data.
* Preserves all input columns while adding vendor-specific columns (`vendor_name`, `vendor_domain`, `source_url`, `first_seen_at`, `last_seen_at`).
* Supports template variables for dynamic domain resolution per row (e.g., `@company_domain`).
* Handles column conflicts automatically with numeric suffixing to avoid overwriting existing data.
* Test mode fetches a single page for fast, deterministic checks before running full-scale enrichment.

***

## 🏁 Getting Started

<Frame>
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/nurturev/images/Get%20Company%20Vendors%20config%20screenshot.png" alt="Get Company Vendors config screenshot" style={{ borderRadius: '0.5rem', width: '100%', margin: '1.5rem 0' }} />
</Frame>

<Steps>
  <Step title="Set Company Domain">Enter a static domain (e.g., `microsoft.com`) or use `@ColumnName` for dynamic row-based resolution.</Step>
  <Step title="Configure Limit">Optionally set the max number of vendor records to fetch. Pagination is handled automatically.</Step>
  <Step title="Run Node">Execute in Test Mode first to preview results, then Standard Mode for full enrichment.</Step>
</Steps>

***

## Inputs

### 🛠️ Required Fields

* **Company Domain (✅)**\
  The domain or URL of the target company (e.g., `microsoft.com` or `https://www.microsoft.com`).\
  *Why it matters:* Determines which company's vendors are retrieved; supports per-row dynamic resolution with `@ColumnName`.

### 🎯 Optional Fields

* **Limit (⚪️)**\
  Maximum number of vendor records to fetch.\
  *Why it matters:* Controls data volume and credit usage while still ensuring you capture enough vendor relationships.

***

## Output

* Adds the following vendor columns to your dataset:\
  `vendor_name`, `vendor_domain`, `source_url`, `first_seen_at`, `last_seen_at`
* Preserves all original input columns.
* Column name conflicts are resolved with numeric suffixes (e.g., `vendor_name` → `vendor_name_1`).

<Note>
  ✨ If any vendor column name conflicts with your input, a numeric suffix is added automatically to preserve all data.
</Note>

***

## How It Works

1. Validate settings and placeholders (`company_domain` must be non-empty or a valid column reference).
2. Load input data if template variables are used.
3. For each row (or static domain), fetch vendor relationships from PredictLeads using pagination.
4. Normalize vendor data to standard columns (`vendor_name`, `vendor_domain`, `source_url`, `first_seen_at`, `last_seen_at`).
5. Merge new data with input columns, resolving any conflicts with suffixes.
6. Output the enriched dataset with all original and new vendor columns.

***

## 🚀 Example Use Cases & Prompts

| Use Case                 | Setup or Prompt Example                                             |
| ------------------------ | ------------------------------------------------------------------- |
| Map partner ecosystem    | Fetch vendors for `microsoft.com` to understand partnerships        |
| Competitive intelligence | Use `@company_domain` column to enrich competitor list with vendors |
| Data enrichment          | Add vendor relationships to your CRM dataset for deeper insights    |

***

## ✨ Pro Tips

<Tip>
  * Use **Test Mode** first to quickly preview a single page of vendor data without consuming excessive credits.
  * Rename output columns if you plan to join with other datasets (`VendorName`, `VendorDomain`) to keep reports clear.
  * When processing multiple rows, reference columns dynamically with `@company_domain` via the Insert Input button.
</Tip>

***

## ⚠️ Important Considerations

<Warning>
  * Large limits in Standard Mode will use more credits.
  * If a static or template-resolved domain is invalid or empty, the node will fail validation.
  * Column conflicts are handled automatically, but review names to ensure consistency in downstream reports.
</Warning>

***

## 🛠 Troubleshooting & Gotchas

| Symptom                     | Likely Cause                          | Quick Fix                                       |
| --------------------------- | ------------------------------------- | ----------------------------------------------- |
| Blank output                | No valid `company_domain` provided    | Verify static domain or input column references |
| Unexpected `_1` suffixes    | Column name conflicts with input      | Rename outputs for clarity                      |
| Fewer vendors than expected | Limit set too low or no vendors found | Increase limit or verify target company domain  |

***

## 📝 FAQ

<AccordionGroup>
  <Accordion title="Can I fetch vendors for multiple companies at once?">
    Yes — use a column with domains (`@company_domain`) as input, and the node will resolve each row dynamically.
  </Accordion>

  <Accordion title="What if a column already exists in my input?">
    New columns will automatically receive a numeric suffix to avoid overwriting.
  </Accordion>

  <Accordion title="How does Test Mode differ from Standard Mode?">
    Test Mode fetches only a single page of results, making it faster and cheaper for validation.
  </Accordion>
</AccordionGroup>

***

## 💰 Pricing

| Action                 | Credit Cost         |
| ---------------------- | ------------------- |
| Row-level vendor fetch | 1 credit per domain |

<Note>
  Credits are consumed per page of results fetched. Using Test Mode helps limit consumption while testing.
</Note>

***

<p style={{ fontSize: '1rem', fontWeight: 'bold', marginTop: '1.5rem' }}>
  Drop this node into your Play to enrich company datasets with vendor insights—automatically. 🚀
</p>