AI Stock Research Without Prompt Glue
Use ApiFinance AI to structure the research loop: gather evidence, compare quality and valuation, generate a clear memo, and keep the name on a watchlist.
What the workflow replaces
Most ad hoc stock research still means copying fields across tabs, screenshots, PDFs, and prompts.
Before
- Separate quote, filing, and statement sources.
- Manual prompt assembly with inconsistent fields.
- No easy way to reproduce the same research path later.
After
- One structured toolchain for profiles, statements, prices, and filings.
- Agent-ready JSON for repeatable memo generation.
- Natural path into saved research and monitoring.
Research workflow
The goal is not more raw data. The goal is a repeatable path from evidence to judgment.
Step 1
Search and resolve the right symbol before analysis starts.
Step 2
Pull profiles, statements, price history, and filing metadata into one working set.
Step 3
Generate a structured research memo or comparison table from grounded JSON.
Step 4
Save the name to a watchlist and revisit after price moves or earnings.
Typical report outputs
A good stock report page should help the user decide what deserves more attention and why.
Structured outputs
- Company quality summary
- Valuation context and multiple compression risk
- Revenue, EPS, and free cash flow trend review
- Key SEC filings to read next
Example prompt
Compare Apple and Microsoft over the last five annual periods.
Highlight margin durability, free cash flow strength, valuation context, and the latest major filing links.
Return a concise research memo plus a comparison table.