Parallel Research

Overview

Deep web research, competitive intelligence, entity discovery, and data enrichment using Parallel AI's specialized APIs.

Quick Decision Tree

What do you need? │ ├── Quick factual answer (3-5 seconds) │ └── Chat API ($0.005/request) │ └── Script: scripts/parallel_research.py chat "question" │ ├── Comprehensive research report (5min-2hr) │ └── Deep Research API ($0.30/report for ultra) │ └── Script: scripts/parallel_research.py research "topic" │ ├── Find entities matching criteria (companies, people) │ └── FindAll API ($0.03 + $0.10/match) │ └── Script: scripts/parallel_research.py findall "query" │ └── Enrich existing data (add fields to records) └── Task API with schema ($0.025/record for core) └── Script: scripts/parallel_research.py enrich data.csv

Environment Setup

Required in .env

PARALLEL_API_KEY=your_api_key_here

Get your API key: https://platform.parallel.ai/settings/api-keys

Common Usage

Quick Q&A

python scripts/parallel_research.py chat "What is Anthropic's latest funding round?"

Deep Research Report

python scripts/parallel_research.py research "Competitive landscape of AI code editors in 2025" --processor ultra

Find Companies

python scripts/parallel_research.py findall "AI code editor companies that raised funding in 2024-2025" --limit 50

Basic Research (Simplified)

python scripts/basic_research.py "Company Name"

Vendor Selection

python scripts/vendor_selection.py "CRM software" --requirements "enterprise,API,automation"

Processor Tiers

Processor Cost/1K Latency Best For

lite

$5 10-60s Basic metadata

base

$10 15-100s Simple research

core

$25 1-5min Cross-referenced research

pro

$100 2-10min Exploratory research

ultra

$300 5-25min Deep research (recommended)

ultra-fast

$300 2-10min Speed + quality

Cost Estimates

Task API Cost

100 quick questions Chat $0.50

Market research report Deep Research (ultra) $0.30

Find 50 competitors FindAll (core) ~$5.00

Enrich 100 leads Task (core) $2.50

Free Tier

20,000 requests free (combined across all APIs).

Security Notes

Credential Handling

• Store PARALLEL_API_KEY in .env file (never commit to git)

• Regenerate keys at https://platform.parallel.ai/settings/api-keys

• Never log or print API keys in script output

• Use environment variables, not hardcoded values

Data Privacy

• Research queries are sent to Parallel AI servers

• Research outputs may contain third-party company information

• Results are stored locally in .tmp/ directory

• Parallel AI may log queries for service improvement

• Avoid including sensitive internal data in research queries

Access Scopes

• API key provides full access to all research endpoints

• No granular permission scopes available

• Monitor usage and costs via Parallel AI dashboard

Compliance Considerations

• Data Sources: Research pulls from public web sources

• Citation: Always cite sources in research outputs

• Accuracy: AI-generated research should be verified

• Competitive Intel: Ensure competitive research complies with policies

• Third-Party Data: Respect intellectual property of sources

• PII in Results: Research results may contain company/individual PII

• Data Freshness: Verify currency of time-sensitive information

Troubleshooting

Common Issues

Issue: Processor timeout

Symptoms: Request times out or returns partial results Cause: Complex query requiring more processing time than allowed Solution:

• Use a faster processor tier (lite or base instead of ultra )

• Simplify the research query

• Break complex queries into multiple smaller requests

• Increase timeout in script if configurable

Issue: Credits exhausted

Symptoms: "Insufficient credits" or quota error Cause: Account credits depleted Solution:

• Check balance at https://platform.parallel.ai/dashboard

• Upgrade plan or purchase additional credits

• Use lower-cost processor tiers for less critical queries

• Monitor usage to avoid unexpected depletion

Issue: Invalid response format

Symptoms: JSON parsing error or unexpected response structure Cause: API returned error or malformed response Solution:

• Check query format matches API requirements

• Retry the request (may be transient issue)

• Verify API key is valid and active

• Review API documentation for expected response format

Issue: Empty or irrelevant results

Symptoms: Research returns no results or off-topic content Cause: Query too narrow, ambiguous, or poorly structured Solution:

• Broaden the search query

• Add context to clarify query intent

• Try different phrasing or keywords

• Use Chat API first to validate query understanding

Issue: API authentication failed

Symptoms: "Invalid API key" or 401 error Cause: API key expired, invalid, or not set Solution:

• Regenerate key at https://platform.parallel.ai/settings/api-keys

• Verify PARALLEL_API_KEY is set correctly in .env

• Check for leading/trailing whitespace in key

• Ensure key has not been revoked

Issue: Rate limited

Symptoms: 429 error or "rate limit exceeded" Cause: Too many concurrent requests Solution:

• Add delays between requests

• Reduce parallel request count

• Implement exponential backoff

• Contact support for higher rate limits if needed

Resources

• references/api-guide.md - Complete API documentation

• references/basic-research.md - Simple company research

• references/vendor-selection.md - Vendor comparison workflow

Integration Patterns

Research to Report

Skills: parallel-research → content-generation Use case: Create polished reports from research findings Flow:

• Run deep research on topic/company

• Generate structured research output

• Format into branded document via content-generation

FindAll to CRM

Skills: parallel-research → attio-crm Use case: Populate CRM with discovered companies Flow:

• Use FindAll to discover companies matching criteria

• Enrich each company with additional data

• Create/update company records in Attio CRM

Research to Sheets

Skills: parallel-research → google-workspace Use case: Build research database in Google Sheets Flow:

• Run FindAll or batch research on multiple entities

• Structure results as tabular data

• Upload to Google Sheets for team collaboration