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Parallel Data Enrichment
BSecurityStructured company and entity data enrichment using Parallel AI Task API with core/base processors. Returns typed JSON output. No binary install — requires PARALLEL_API_KEY in .env.local.
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- Added October 17, 2026
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88/100- Sends environment variables or credentials to an external URL
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[](https://www.skillsdirectory.com/skills/diegosouzapw-parallel-data-enrichment)---
name: parallel-data-enrichment
description: "Structured company and entity data enrichment using Parallel AI Task API with core/base processors. Returns typed JSON output. No binary install — requires PARALLEL_API_KEY in .env.local."
compatibility: Requires PARALLEL_API_KEY in .env.local. Uses curl. Takes 15s-5min.
metadata:
author: harshanandak
version: "1.0.0"
---
# Parallel Data Enrichment
Enrich company or entity data into structured JSON using the Task API. Use `core` (1-5 min, $0.025) or `base` (15-100s, $0.01) for structured output.
> **CLI alternative (recommended)**: Install `parallel-cli` for official skill:
> `npx skills add parallel-web/parallel-agent-skills --skill parallel-data-enrichment`
## Setup
```bash
API_KEY=$(grep "^PARALLEL_API_KEY=" .env.local | cut -d= -f2)
```
## Create Enrichment Task
```bash
curl -s -X POST "https://api.parallel.ai/v1beta/tasks/runs" \
-H "x-api-key: $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "OpenAI",
"processor": "core",
"output_schema": {
"type": "object",
"properties": {
"name": {"type": "string"},
"founded_year": {"type": "integer"},
"headquarters": {"type": "string"},
"employee_count": {"type": "integer"},
"key_products": {"type": "array", "items": {"type": "string"}}
}
}
}'
```
Response: `{"id": "task_abc123", "status": "queued"}`
## Check Result
```bash
curl -s "https://api.parallel.ai/v1beta/tasks/runs/task_abc123" \
-H "x-api-key: $API_KEY"
```
```json
{
"id": "task_abc123",
"status": "completed",
"result": {
"content": {
"name": "OpenAI",
"founded_year": 2015,
"headquarters": "San Francisco, CA",
"employee_count": 770,
"key_products": ["ChatGPT", "GPT-4", "DALL-E", "Whisper"]
},
"basis": {
"citations": [{"url": "...", "excerpt": "..."}]
}
}
}
```
## Processors
| Processor | Speed | Cost | Use For |
|-----------|-------|------|---------|
| base | 15-100s | $0.01/task | Quick lookups, simple data |
| core | 1-5 min | $0.025/task | Enrichment, verification, structured data |
## Tips for output_schema
- Keep schemas simple — fewer fields = more reliable
- Use `"type": "string"` broadly; avoid strict enums
- Omit optional fields from the schema
## When to Use
- Company or person data enrichment
- Structured data extraction with typed schemas
- Lead qualification, CRM enrichment, research
For narrative reports, use `parallel-deep-research`. For web search, use `parallel-web-search`.
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