ChatGPT Plugin

Deep Document Search

Search your documents with AI

Brand: Forest AI

Category: AI
Primary Subcategory: Enterprise Knowledge Search & AI Context Layer

Integration details

Description

Deep Document Search turns ChatGPT into a powerful interface for your private document knowledge base. Search and analyze PDFs, Word files, scanned documents, and large document collections using natural language; find relevant information across thousands or millions of files; and get accurate, traceable answers with citations back to the original documents. It is built for document-intensive workflows such as legal research, regulatory compliance, corporate knowledge, due diligence, research, and document analysis.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: AI
Primary Subcategory: Enterprise Knowledge Search & AI Context Layer
Secondary Subcategories: None listed
Brand: Forest AI
Access: Account required
First tracked: 2026-09-19
Tool count: 12
Market: US

Agent DiscoverabilityChatGPT Discoverability ScoreUpdated daily

The first to track the ChatGPT, Claude, Muse, Grok & Google ecosystems, with the largest database on the core platforms. Tracked daily since 1 December 2025.

Deep Document SearchChatGPT Plugin · Enterprise Knowledge Search & AI Context Layer

Discoverability Score

0/100

Invisible

Category rank

#22of 75

in Enterprise Knowledge Search & AI Context Layer

Picked: 0.0/100
Found: 0.0/100
Positioned: –/100

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Category leaderboard

Enterprise Knowledge Search & AI Context Layer

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Primary Subcategory

Competing in ChatGPT Enterprise Knowledge Search & AI Context Layer

View Category

Listed in alphabetical order

Primary Subcategory

AgentContext0/100

Algolia Productivity0/100

Analytics Brain0/100

Archiveye0/100

Atlan0/100

Deep Document Search0/100

Tools

12 tools agents can invoke

Inspect a dataset: stable field IDs, types, dimension/measure roles, row count, and supported chart types. Use field IDs (never display names) in run_analysis.
describe_dataset
Load a saved chart (exploration) definition and revision with a first-party view link.
get_chart
Retrieve the full text content of one or more items by their item_ids (returned by search_documents). An item groups one or more documents together â€” a document is a type of item. Use this when the user asks to read the complete content of specific documents/items found via search. Content is fetched from the item content store in a single batch; pass up to 20 item_ids.
batch_get_item
Poll a query job: status plus bounded typed rows, columns, truncation flag, dataset version, and provenance when terminal.
get_query_result
List analytics-ready datasets in the organization. Returns dataset IDs and names with conversion status. Resolve names to IDs here before calling other tools.
list_datasets
List projects in your organization. Optionally pass workspace_id to see only the projects inside that workspace, and/or project_name to fuzzy-match only the projects whose name contains that text (case-insensitive substring match, e.g. "annual" also finds "Annual Budget"). Returns project IDs, names, and workspace IDs. Use the IDs to scope a document search (pass them to search_documents via project_ids).
list_projects
List workspaces in your organization. Optionally pass workspace_name to fuzzy-match only the workspaces whose name contains that text (case-insensitive substring match, e.g. "fin" also finds "Finance"). Returns workspace IDs and names. Use the IDs to scope a document search (pass them to search_documents via workspace_ids) or to filter projects (pass one to list_projects as workspace_id).
list_workspaces
Validate a visualization spec against a completed job's columns and return the portable chart spec. Requires chart IDs from describe/get results, never invented names.
preview_chart
Bounded column statistics (min/max/avg/distinct counts/null rates). Never returns raw rows. Use it to pick sensible filters and aggregations.
profile_dataset
Persist a chart definition (query + visual spec) under a name. Returns the chart ID, revision, and first-party view URL.
save_chart
Keyword search across the user's uploaded documents. Returns relevance-ranked results with scores, highlighted matching passages (snippets), item IDs, and match fields (description, mime type, workspace/project). Provide one or more short, specific phrases via the `phrases` array (e.g. 2-4 key words, not full sentences) â€” documents matching any phrase are returned; exact phrase matches are tried first, and if nothing matches the tool retries by matching individual words. You can control how much context you get by setting `highlight_length` (characters per highlighted snippet, default 450) â€” use a larger value (e.g. 2000-4000) when you need more surrounding information to answer a detailed question, and `num_snippets` to control how many snippets per result are returned (default 3). You can restrict results by passing arrays of item_ids, project_ids, or workspace_ids: within each array IDs are combined with OR (match any), and the groups are combined with AND (e.g. (item1 OR item2) AND (project1 OR project2)).
search_documents
Candidate questions with executable draft specs for a dataset. Suggestions are questions, not findings — run one before claiming any trend.
suggest_analyses

FAQs

Deep Document Search ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Deep Document Search's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Deep Document Search alternatives on ChatGPT?

As of 2026-11-02, Deep Document Search competes with Dropbox Dash, AgentContext, Algolia Productivity, Analytics Brain, Archiveye, Atlan, Big Documents Agent, BitsWeave and 66 more in ChatGPT Enterprise Knowledge Search & AI Context Layer, ranked by public Discoverability Score.

Where does Deep Document Search rank in Enterprise Knowledge Search & AI Context Layer on ChatGPT?

As of 2026-11-02, Deep Document Search ranks #22 of 75 in ChatGPT Enterprise Knowledge Search & AI Context Layer with a Discoverability Score of 0/100 (Invisible).

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.

Get alerts for Deep Document Search

Competing in ChatGPT Enterprise Knowledge Search & AI Context Layer

12 tools agents can invoke

Deep Document Search ChatGPT Plugin FAQ