AI & extraction

How a list becomes structured data.

Paste a list. Toolsy pulls out item names, quantities, units, and specs. You see every line before an RFQ draft is prepared.

Reads messy listsShows source textManual send
Reference catalog67 items
DirectoryReference listings by category
ReadingRules first, model optional
OutputLine items with source text
Pipeline

From a site note to a quote package.

Each step can be checked on its own. Without an API key, the parser runs alone.

01

Paste

Paste a list or upload a text file.

TEXT · CSV
02

Read

Toolsy pulls out item names, quantities, units, and specs.

STRUCTURED LINES
03

Check

You see every line before an RFQ draft is prepared.

YOUR CHECK
04

Match

Each line is compared with a reference directory of 67 catalog items.

REFERENCE DIRECTORY
05

Draft

One RFQ email per supplier, ready to send from your own mailbox.

RFQ DRAFT
Safeguards

The rules the model works under.

When the model output does not fit, the workspace falls back to the parser. It does not guess to fill a gap.

Rules take over when needed

If the model output does not fit, the parser result is used.

Source lines stay attached

Every extracted line keeps the original text beside it, so you can compare the two.

You choose the supplier

Toolsy never picks a winner. It ranks listings and shows the trade-offs; you select the supplier.

No training on your text

Toolsy does not use workspace text to train models. Your model provider's terms still apply.

Checking a result

Read each line before you send.

Each extracted line keeps the source text it came from, so you can compare the two side by side.

Source line

300 pcs 4-inch PVC pipe AW class

Extracted
Name
PVC pipe
Spec
4-inch · AW class
Quantity
300 pcs
Category
Plumbing & Pipe
For developers

Any OpenAI-compatible endpoint works. The provider and model are set per deployment.

TaskVolumeUse
Material-list extractionOne model pass per list, when configuredSchema-validated JSON output
RFQ draft rewriteOptional, one pass per draftPlain-text subject and body; template fallback
Catalog matchingReference catalog, refreshed by handName and alias matching

Next.js · Postgres · OpenAI-compatible inference · [email protected]

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