Deep Research
Analyst-grade investigation across companies, industries, and financial topics — web, filings, earnings transcripts, and market data cross-verified into one cited brief.
Methodology
Scope the question
Before any data is pulled, the core question, time horizon, and market coverage are fixed. Scoping converts a vague prompt like "research NVDA" into a targeted plan — company vs industry lens, recent-quarter vs long-term trend, single market vs cross-market — so downstream collection stays focused instead of exhaustive.
Parallel multi-source collection
Evidence is gathered in parallel across web search (neural for broad queries, keyword for precise ticker and phrase matches), article and transcript retrieval, SEC filings, earnings call transcripts, and structured financial data. No single source is trusted alone; the breadth is the point.
Cross-verify and filter noise
Claims are compared across sources — anything that lands from only one source is flagged as unverified. Facts (earnings numbers, price data) are separated from opinions (ratings, commentary); stale items are flagged by publication date.
Synthesize into an analyst-style brief
Findings are collapsed into a structured report covering key findings, recent developments, financial snapshot, market sentiment, risks, and cited sources — delivered as a downloadable file so the chat stays clean and the full analysis is reviewable.
Example prompts
- “Do a deep dive on MSFT — what’s driving growth and where are the risks?”
- “Research the AI-chip industry — who’s winning, who’s losing, and why?”
- “Summarize this YouTube earnings call and extract the key investment takeaways.”
- “Read this article on the AI-capex cycle and pull the investment angle.”