The Perplexity API for Automated Research

Why Use the API?

The Perplexity API lets you programmatically query Perplexity's models, enabling:

• Scheduled competitive intelligence reports
• Automated market monitoring
• AI agent research pipelines
• Bulk research at scale

The API uses OpenAI-compatible format, making integration straightforward.

Basic API Call

import requests

response = requests.post(
    "https://api.perplexity.ai/chat/completions",
    headers={"Authorization": f"Bearer {PERPLEXITY_API_KEY}"},
    json={
        "model": "llama-3.1-sonar-large-128k-online",
        "messages": [
            {"role": "user", "content": "What are the latest developments in enterprise AI governance?"}
        ],
        "search_recency_filter": "week",
        "return_citations": True
    }
)

result = response.json()
answer = result["choices"][0]["message"]["content"]
citations = result["citations"]

Model Selection

Building a Weekly Intelligence Report

topics = [
    "AI governance regulatory updates",
    "Enterprise AI adoption trends",
    "Key competitor product launches"
]

report = []
for topic in topics:
    response = query_perplexity(topic, recency="week")
    report.append({"topic": topic, "findings": response})

send_weekly_brief(report)

Recency Filters

The search_recency_filter parameter controls how fresh sources must be:

• "hour" — breaking news
• "day" — last 24 hours
• "week" — last 7 days
• "month" — last 30 days

For competitive intelligence, "week" balances freshness with coverage.

Rate Limits and Cost

The API charges per token. Budget $50–200/month for a moderate automation pipeline. Use caching aggressively — many research queries repeat with minor variations.