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Our market intelligence agent intelligently routes queries to the most appropriate specialized agents for comprehensive analysis.
- Decides which specialized Octagon agent to call.
- Handles multi-step queries automatically
Public Market Agents
Our public market intelligence agents provide comprehensive analysis of publicly traded companies through SEC filings, earnings call transcripts, stock data, and financial metrics.
Private Market Agents
Our private market intelligence agents deliver insights on private companies, including funding rounds, M&A transactions, investor profiles, and debt activities.
Our deep research agents provide powerful capabilities for extracting data from websites and conducting comprehensive market research.
- Conducts end-to-end investment research.
- Aggregates from multiple databases, filings, and live web data.
- Produces multi-section reports (overview, market trends, risks, opportunities).
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
Capabilities
- Extract structured financial data from investor relations websites
- Parse tables and financial statements from online sources
- Convert unstructured web data into structured formats
- Navigate multi-page financial resources
- Support for regional localization parameters
Use Cases
The Scraper Agent is best for:
- Gathering financial data from websites that don’t have accessible APIs
- Extracting data from investor relations portals
- Collecting pricing information from e-commerce sites
- Gathering real estate listing data
- Compiling structured data from financial information portals
Example Queries
- “Extract all data fields from zillow.com/san-francisco-ca/ max_pages:2”
- “Extract all data fields from www.carvana.com/cars/ country:us”
Gathers structured & unstructured financial data from live web sources.
Ex:”Scrape top 10 headlines affecting crude oil prices I the last 24 hrs.
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Investment criteria, fund details, and past activities
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Management team, investors, lenders, service providers
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Deal metrics for funding, M&A, IPO, debts transactions
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Comprehensive company information and financials
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Happy clients
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ONE AI Tim FisherAI Developer
Learning Alan BeghamCEO Neuro