AI Stock Research Tools: An Honest Category Map
An honest map of AI stock research tools: data terminals, visual report tools, general assistants, and where a verification-layer thesis check fits.
There are many AI research tools for stocks and I want to know which kind does what before I pick one for my workflow.
Most tools fall into three groups: data terminals like Fiscal.ai, TIKR, and Koyfin; visual report tools like Simply Wall St; and general assistants like ChatGPT and Perplexity. A verification layer like ThesisCheck sits after all three: it checks the thesis you formed against the filings.
Four kinds of tools, four different jobs
The category is easier to navigate once the jobs are separated. Each group below is genuinely good at its own job, and none of them replaces the others.
- Data terminals (Fiscal.ai, TIKR, Koyfin): deep fundamentals, screening, charting, and model-ready financial data.
- Visual report tools (Simply Wall St): standardized, readable company snapshots and portfolio views.
- General assistants (ChatGPT, Perplexity): drafting, brainstorming, and fast answers across any topic.
- Verification layer (ThesisCheck): a one-off check of your written thesis against public filings, with receipts, a forced bear case, and gaps.
What each category is built for
Fast access to fundamentals, estimates, screens, and charts across thousands of tickers.
The data does not say whether your specific thesis claims hold up; you still map numbers to claims yourself.
A consistent, visual company snapshot that is easy to read and compare.
The template is company-shaped, not thesis-shaped, so your written claim set is not what gets tested.
Drafting, summarizing, and answering follow-up questions in seconds.
Fluent answers can blend supported facts with unsupported claims unless you audit every citation yourself.
Checking one written thesis against filings: receipts, forced bear case, coverage audit, evidence gaps.
It is episodic and single-thesis by design; it is not a data terminal, screener, or portfolio tracker.
How the categories combine in practice
The tools are complements, not substitutes. A common workflow uses one from each group at a different stage.
Use a data terminal to pull fundamentals, comparables, and history for the companies you care about.
Use a visual report tool for a standardized overview and to spot what stands out.
Use an assistant to sharpen the argument and write down what you actually believe and why.
Run the written thesis through a falsification check so support, bear-case pressure, and missing evidence are separated with receipts.
What the verification step adds
A verification layer sits after data terminals, visual reports, and assistants: it takes the thesis those tools helped you form and checks it against the filings.
Evidence summary: The artifact keeps the check inspectable: each material claim carries a source label, date, and locator, the bear case is forced, and unproven claims are marked as gaps.
Public sources referenced for this overview
Public product reference for Fiscal.ai as a financial data and research terminal.
TIKRTIKR website2026-07-05Public product reference for TIKR as a fundamentals data and screening terminal.
KoyfinKoyfin website2026-07-05Public product reference for Koyfin as a market data, charting, and analytics platform.
Simply Wall StSimply Wall St website2026-07-05Public product reference for Simply Wall St as a visual company-report and portfolio platform.
OpenAIChatGPT product page2026-07-01General product reference for ChatGPT as a broad assistant workflow, not a dedicated ThesisCheck report artifact.
PerplexityPerplexity product page2026-07-05General product reference for Perplexity as an answer-engine assistant workflow.
Go deeper on the comparisons
How a source-checked thesis stress test differs from a general chatbot workflow.
ThesisCheck vs Simply Wall StHow a standardized visual company report differs from a thesis falsification check.
Open the sample reportInspect the verification-layer artifact: receipts, bear case, coverage audit, and gaps.