The Table Extraction Tool
Detect and extract tables from documents, PDFs, and images into structured rows and columns so an agent can compute over tabular data that was trapped in a page or a scan.
Most of your content isn’t text
Calls, recordings, scans, images, and foreign-language documents carry critical information that text-only agents simply can’t use. Turning that media into data usually means shipping sensitive content to a hosted API — exactly what regulated teams can’t do.
Media is opaque
Audio, video, and images are invisible to search and to agents.
Language barriers
Content in other languages stays out of reach.
Manual transcription
Transcribing and translating by hand is slow and costly.
Sensitive content
Calls and scans can’t be sent to a third-party service.
Table Extraction, without the risk
Capability
What it does
Lift tables out of documents and images.
it detects and extracts tables from documents, PDFs, and images into structured rows and columns.
Assignable to any agent
How it works
Predictable, inspectable behavior
Designed to be reliable.
it recovers table structure — headers, rows, cells — inside your perimeter, so tabular data trapped in a page or scan becomes computable data.
Every call logged
Governance
Private, governed, on-premise
Runs inside your perimeter.
Transcription, translation, and analysis can run on local models inside your perimeter with audit logging, so sensitive audio, video, and documents become usable data without ever leaving your environment.
Per-tenant, logged
Parameters
The table_extract tool accepts these inputs when an agent calls it. Required inputs are flagged.
How the Table Extraction tool works in practice
Table Extraction is a multimodal tool you assign to a VDF AI agent. It detects and extracts tables from documents, PDFs, and images into structured rows and columns. Its hallmarks — Tables, Structured, From images — let an agent rely on it as a dependable step in a larger task rather than a brittle one-off script.
Under the hood, it recovers table structure — headers, rows, cells — inside your perimeter, so tabular data trapped in a page or scan becomes computable data. Every call is scoped to the requesting tenant and written to an audit log, so the capability is safe to run inside a regulated, on-premise environment — the same governance model behind every VDF AI tool.
Teams reach for Table Extraction when they need to handle financial docs, scanned forms, and reports. It rarely works alone — pair it with PDF Extract, Document Parser, and XLSX Parser to build a complete, governed workflow, then compose those steps into an on-premise VDF AI Network.
Where Table Extraction pays back
Financial docs
Pull figures out of a statement or filing.
Scanned forms
Turn a scanned table into data.
Reports
Extract tables for analysis or reconciliation.
Migration
Digitize tables from legacy documents.
Assigned to agents, orchestrated as networks
On VDF AI, an industry’s use cases map to agents, and you assign tools like this one to those agents. Compose multiple agents into a governed, on-premise network.
What changes after you assign it
Questions about the Table Extraction tool
What is the Table Extraction tool?
It detects and extracts tables from documents, PDFs, and images into structured rows and columns. Assigned to a VDF AI agent, it runs under role-based policy with full audit logging so the capability is safe to use in production.
Can it extract from images and scans?
Yes. It recovers table structure from images and scanned pages, not just digital documents.
What does it return?
Structured rows and columns you can compute over, with headers preserved.
What inputs does the Table Extraction tool need?
It has no strictly required inputs, and optionally accepts source, file_base64, and page. Each parameter is validated when an agent calls the tool, and the full call is logged for audit.
Which tools pair well with Table Extraction?
Table Extraction is commonly assigned alongside PDF Extract, Document Parser, and XLSX Parser. On VDF AI you compose several tools and agents into a single governed, on-premise network.
Does it run on-premise?
Yes. Like every VDF AI tool, it can run on-premise or in your sovereign cloud, scoped per user and audit-logged, so your data never leaves your perimeter.
How do agents use it?
You assign the tool to an agent under a role-based policy; the agent calls it as one step in a task, and several agents and tools can be orchestrated together as a governed VDF AI Network.
Assign Table Extraction to these agents
These VDF AI agents can be assigned this tool. Open an agent to see the full toolkit it can run.
Tools that work well alongside this one
Where this tool delivers value
Put Table Extraction to work
See the Table Extraction tool assigned to an agent and orchestrated in a governed, on-premise network.