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Octagon Deep Research Agent ​

Model Name: octagon-deep-research-agent

A comprehensive agent that can utilize multiple sources for deep research analysis.

Key Capabilities ​

  • End‑to‑End Research Pipeline → One Call. Fully-managed orchestrating scrapers, LLMs, summarizers, and vector stores. The agent decomposes the query, explores the web & premium data feeds, and synthesizes the answer for you.
  • Low Latency Complete all deep research tasks in less than 30 secs
  • Optimized for Quality Synthesize 3x more sources than incumbent solutions with a focus on high domain authority financial and market sources
  • Structured Output. Supports json, csv, txt, md
  • Source Attribution. Every insight is tied back to a URL so you can trust—and audit—the result.

Use Cases ​

The Deep Research Agent is best for:

  • Deep investment research questions requiring up-to-date aggregated information
  • Comprehensive analysis of market trends and industry developments
  • Connecting financial performance with qualitative factors
  • Understanding the impact of external events on companies and sectors
  • Developing investment theses with multiple supporting data points

Example Prompts ​

  • IPO analysis "Analyze Chime Financial’s prospective IPO using its S-1 and the full universe of publicly available analyst research (equity notes, industry primers, media interviews, podcasts, X, etc.). Deliver a comprehensive yet concise report that is suitable for an institutional investor’s investment memo."
  • Event study: "Research the financial impact of Apple's privacy changes on digital advertising companies' revenue and margins"
  • Competitive positioning: "Analyze the competitive landscape in the cloud computing sector, focusing on AWS, Azure, and Google Cloud margin and growth trends since 2022"
  • Thematic deep dive: "Investigate the factors driving electric vehicle adoption and their impact on battery supplier financials"
  • Cross‑market impact: "How will rising copper prices affect the gross margins of EV manufacturers and renewable energy companies over the next 12 months?"

Code Examples ​

Python
response = client.responses.create(
    model="octagon-deep-research-agent",
    input="Research the financial impact of Apple's privacy changes on digital advertising companies' revenue and margins",
)
JavaScript
const response = await client.responses.create({
  model: "octagon-deep-research-agent",
  input: "Research the financial impact of Apple'\''s privacy changes on digital advertising companies'\'' revenue and margins",
});
cURL
curl -X POST https://api-gateway.octagonagents.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-octagon-api-key" \
  -d '{
    "model": "octagon-deep-research-agent",
    "input": "Research the financial impact of Apple'\''s privacy changes on digital advertising companies'\'' revenue and margins",
    "stream": true
  }' \
  --no-buffer