Document Search — Complete Guide

Document Search is how you find the source material behind your research. From one search box you can look across AllMind’s whole library of market documents — US and Canadian filings, earnings call transcripts and slides, press releases, sell-side and ESG research, sector data, news, and investor-relations materials — plus your own uploaded documents. You can search the literal way (find every document that contains an exact word or phrase) or the meaning-based way (find the most relevant passages even when the wording differs), read any result in-app with your terms highlighted, and hand a document — or a whole set of results — to the AI assistant for a cited answer. Find it in the left sidebar under Document Search, alongside Data Room, Grids, and Reports.

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When to use it

Reach for Document Search when:

• You need to find specific source documents — “the latest 10-K,” “every transcript that mentions a plant closure,” “recent sell-side notes on this name.”
• You want to locate an exact word, name, or phrase across thousands of documents (a person, a counterparty, a product, a covenant term).
• You want a fast, cited answer drawn only from real documents, with the sources attached so you can verify every claim.
• You’re gathering the raw material for a deeper piece of work — sources you’ll save to a Data Room, analyze in a Grid, or turn into a Report.

Use something else when:

• You want a quick fact or an open-ended back-and-forth across all your sources → Chat.
• You have an open-ended question that needs genuine multi-step research and a deliverable → Agent Studio.
• You want the same questions answered consistently across many companies or documents → Grids.
• You want a formatted, templated write-up as the main output → Reports.
• You want to organize and reuse a set of documents as their own analysis universe → Data Room (Document Search is how you find documents to put there).

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How to use it

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Search modes — exact vs. meaning vs. AI

There are four modes, split into a Keyword option and an AI Search option that expands into three depths:

• Keyword (default) — finds documents that literally contain your word or phrase, with every hit highlighted. Matching is whole-word and case-insensitive, so “report” won’t match “reporting.” Add several terms and a document must contain all of them. Best for pinpointing exact mentions of a name, term, or phrase. No AI answer; results are ranked by how many times your terms appear, and you also see a library-wide count of total mentions.
• Semantic — searches by meaning rather than exact wording, returning a focused, highly relevant set of passages each with a relevance score. Best for discovering material on a concept or theme when the exact words vary. No AI answer.
• Ask AI — runs a meaning-based search and then automatically opens the assistant and answers your question using the documents it found, with citations you can click through to the source. Best when you want a quick, grounded answer to a specific question.
• Deep Dive — runs a broader meaning-based search and produces a fuller, more thorough synthesis across many more documents, with deeper reasoning. Best for a comprehensive, multi-document briefing — it reads more and takes a little longer.

Rule of thumb: use Keyword when you know the exact term you’re hunting for; use Semantic to browse by topic; use Ask AI for a fast cited answer; step up to Deep Dive when the question is broad enough to be worth reading across many documents.

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What you can search (sources & document types)

Document Search covers AllMind’s curated library of market documents, plus your own uploads. You can search everything at once or narrow to any combination of these sources: A few things worth knowing:

• Leaving every source unselected searches the whole library — but your private Data Room is never included unless you explicitly select it, so your own documents stay separate by default.
• Your Data Room results are private to you. Documents you upload to a Data Room become searchable here only after they finish processing, and only for your account.
• Canadian tickers are handled for you — you don’t need to worry about exchange suffixes when searching SEDAR filings or research.
• News by sentiment (bullish vs. bearish coverage) is available through the News templates rather than a manual sentiment filter.

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Filtering, company scope, and templates

• Company scope — pick a ticker (by symbol or company name) and Document Search pre-fills that company across all the relevant sources at once, so you don’t have to set it per source.
• Date range — filter by publish date with quick presets (today, this week, this month, this quarter, year to date, past year) or a custom range. It applies to every mode. You can’t select a future date.
• Per-source “Only” shortcut — restrict a search to just one source in a click.
• Reset — clear all filters; an active-filter count shows how focused your current search is.

Templates are the fastest way to start. Document Search ships with a large set of prebuilt, expert-written searches, grouped by the kind of work you do — with the most useful surfaced under Recommended:

• Research & Analysis — sell-side research, industry positioning, bull/bear thesis
• Earnings & Guidance — earnings results, forward guidance, growth drivers
• SEC/SEDAR Filings — 10-K deep dive, 10-Q analysis, 8-K events, proxy & governance, SEDAR filings
• Investor Relations — investor days, conference transcripts and slides, capital markets days, analyst days
• ESG & Sustainability — ESG performance, ESG risk assessment
• News & Sentiment — recent developments, bullish catalysts, risk flags
• Industry & Sector — market data, competitive landscape
• By mandate — Long Only (quality compounders, dividends, capital allocation), L/S Equity (short thesis, earnings quality, relative value, catalysts, insider signals), Fixed Income (credit profile, maturities, liquidity, covenants, recovery), and Private Equity (LBO screening, value creation, add-ons, management diligence)

Each template fills in an optimized query and pre-selects the right sources and filters, and runs as a Deep Dive. Scope it to a company and it tailors the dates to that company’s fiscal calendar.

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Reading and working with a document

Select any result and it opens in the viewer on the right:

• Readable in-app: PDFs, web/HTML pages (in a clean Reader Mode, on by default — switch to “Original View” any time), earnings and IR transcripts (laid out speaker-by-speaker), and news articles.
• Your terms are highlighted inside the document, PDFs jump to the most relevant page, and you can step through every match with next/previous (or the in-document find box on PDFs).
• Download the open document — PDFs download with a light watermark showing your account, transcripts download as text, and news opens the original article. Other file types (such as spreadsheets, Word, or PowerPoint in your own Data Room) can be downloaded even when they aren’t rendered in the viewer.
• Save it — bookmark a single document, or save all current results at once, into your Data Room to build a reusable set of sources.
• Copy as citation — in Keyword mode, copy a result’s snippet as a clean, formatted citation (quote, source, date, title).

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Bringing in the AI

Document Search is a natural on-ramp to the AI assistant, in three ways:

1. Ask AI / Deep Dive modes automatically open the assistant and answer your query using the documents the search found — grounded only in those documents, with clickable source citations.
2. “Analyze with AI” sends all of your current results to the assistant at once and asks your search question for you (available in the meaning-based modes).
3. “Add to AI Chat” on an open document loads that single document’s full text into the assistant for focused follow-up questions.

In all three cases the assistant answers strictly from the documents you gave it — it doesn’t go off to the web or run a broader research job — so the answer stays scoped to exactly what you searched, and every claim traces back to a source you can open. Comparison questions come back as tables with figures tied to their source rows and dates.

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Tips & best practices

• Match the mode to the task. Hunting for an exact term? Keyword. Exploring a topic? Semantic. Want an answer? Ask AI, or Deep Dive for breadth.
• Keyword is literal. It matches whole words, so search the root term you expect to appear, and remember that multiple terms must all be present in the same document.
• Narrow before you go deep. Setting a company, a couple of sources, and a date range makes both the results and the AI’s answer sharper — especially for Deep Dive.
• Start from a template when you’re not sure how to phrase a research question; then tweak the filled-in query.
• Save as you go. Bookmark the documents worth keeping into a Data Room so your sources are ready for the next step (a Grid, a Report, or further analysis).
• Verify with the citations. The AI answers are grounded in real documents — click the sources to confirm the numbers before you rely on them.

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Limits & things to know

• Keyword matching is whole-word and case-insensitive — “report” will not match “reporting,” and multiple terms must all appear in the same document. This is the usual reason a keyword search returns fewer hits than expected.
• Meaning-based searches return a focused set, not everything — Semantic returns the most relevant passages, Ask AI reads up to about 30 documents in full, and Deep Dive reads across roughly 100+ documents (the most relevant in full, the rest summarized). If a search returns far more than the AI can read, the lowest-ranked documents are set aside, and the answer notes that some were omitted.
• The AI modes are single-pass and document-grounded. They answer from the results your search returned — they don’t run multiple rounds or browse beyond those documents.
• Relevance scores appear only in the meaning-based modes; keyword results show match counts instead.
• Dates filter by publication date, and you can’t pick a future date.
• Reader Mode is for web pages, not PDFs, and depends on the page being cleanly parseable; otherwise you’ll see the original view.
• PDF downloads are watermarked with your account details.
• Your recent keyword searches (the last 20) are remembered in your browser for quick re-runs.
• Your Data Room is opt-in and private to you; it’s excluded from a “search everything” run unless you select it.

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How it works with other features

Document Search is the sourcing layer of the research workflow, and it connects to the rest of the platform on both sides:

• Data Room — search your own uploaded documents as a source, and save search results into a Data Room to assemble a reusable set of sources. Documents you add to a Data Room become searchable here once processed.
• Chat — the Ask AI and Deep Dive modes are an entry point into the assistant, and “Analyze with AI” / “Add to AI Chat” hand documents to Chat as cited context. It’s the same assistant you use everywhere.
• Agent Studio — an agent can be given the ability to search this same document library during its runs, so it can find and cite source documents on its own.
• Grids — grid cells can be filled from this same document library, so a document you find here can resurface as a sourced answer in a Grid.
• Reports — report-building draws on the same library to gather cited evidence, so your sources flow through to the finished write-up.

In short: Document Search finds and verifies the sources; Data Room organizes them; Chat, Agent Studio, Grids, and Reports turn them into analysis and deliverables.

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Example workflow: from sources to a finished deck

A real multi-feature journey — “analyze the gold sector and build a presentation”:

1. Find the sources — in Document Search, use the templates and filters to pull the right material on each sub-topic (supply/demand, major producers, cost curves, macro drivers, price outlook, risks): sell-side research, sector data, filings, transcripts, and recent news.
2. Verify and save — open the key documents to confirm they’re on point, then save the best results into a Data Room so the whole source set lives in one place.
3. Organize — keep the project’s documents together in that Data Room as its own analysis universe.
4. Research in depth — fire off Agent Studio runs (or Deep Dive answers) on the meatier sub-topics, grounded in those sources.
5. Structure it — build a Grid to answer the same key questions consistently across the producers or topics.
6. Synthesize — generate a Report from a template, or have an agent produce the deck — every figure traceable back to a document you found in step 1.

The result: a sourced, structured analysis and a finished presentation, assembled across the platform — and grounded in real documents from the very first step.

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Common questions

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Getting help

For help using Document Search or to talk through a research workflow, reach AllMind support through the in-app support option or your account team.