# Segmentation is now $0.50 per 1,000 pages

> We cut the price of document segmentation by 92% — and for the most common use, by 95%.

- Canonical: https://www.datalab.to/blog/segment-pricing
- Published: 2026-08-19
- Authors: Vik Paruchuri

We've cut the price of [document segmentation](https://www.datalab.to/pricing). The Segment processor is now **$0.50 per 1,000 pages**, down from $6.

The effective cut is bigger than it looks. Until now, every segmentation request ran a full document parse first, so a typical job billed Convert plus Segment — $10 per 1,000 pages all-in. Page-level segmentation no longer needs the parse at all, so it bills Segment alone: **$0.50 per 1,000 pages, a 95% reduction** for the most common use.

## The new rates

| Mode | What you get | Before | Now |
| --- | --- | --- | --- |
| Page-level split | Boundaries between combined documents: page ranges, titles, confidence — no OCR text | $10/1k pages | **$0.50/1k pages** |
| Block-level | Boundaries that can fall mid-page, guided by an optional prompt, plus the full parsed markdown | $10/1k pages | **$4.50/1k pages** |

Block-level still runs a Convert alongside segmentation because it returns the parsed document — its rate is Convert ($4) + Segment ($0.50).

## Why the price dropped

This isn't a promotion — we rebuilt the engine. Segmentation now works directly off the raw PDF, using the embedded text layer where one exists and falling back to page images for scans. Splitting a stack of documents doesn't require reading every word on every page, so we stopped charging as if it did. The rebuild also made boundary detection *more* accurate, especially on scanned documents.

The lower price is us passing the savings through.

## Iterating is cheap now too

`/segment` reuses previous parses automatically. If you segment a document your team has already converted — or you re-run with a tweaked schema — we detect it and bill only the segmentation delta, not a fresh parse. You can also pass a `checkpoint_id` from a previous `/convert` call explicitly.

## How to use it

Send a combined PDF to `/segment`. For automatic document-boundary detection at page level:

```python
import time
import requests

headers = {"X-API-Key": "YOUR_API_KEY"}

response = requests.post(
    "https://www.datalab.to/api/v1/segment",
    headers=headers,
    files={"file": open("combined_scans.pdf", "rb")},
    data={"segmentation_schema": '{"segmentation_strategy": "document_boundary"}'},
)
check_url = response.json()["request_check_url"]

while True:
    result = requests.get(check_url, headers=headers).json()
    if result["status"] == "complete":
        break
    time.sleep(2)

for segment in result["segmentation_results"]["segments"]:
    print(segment["name"], segment["pages"], segment["confidence"])
```

For block-level segmentation with a custom rule, pass a granularity and a prompt — boundaries can then fall mid-page, and you get the parsed markdown back:

```python
data = {
    "segmentation_schema": '{"granularity": "block", "prompt": "start a new segment at each invoice"}',
}
```

See the [segment API reference](https://documentation.datalab.to/api-reference/segment-document) for the full request and response shape.

## No action needed

The new rates are live and apply automatically to every request — there's nothing to change on your side. Try it in the [playground](https://www.datalab.to/playground), and check the [pricing page](https://www.datalab.to/pricing) for the full rate card.

If you're splitting large combined files — loan packages, medical records, mailroom scans, discovery productions — the economics just changed by an order of magnitude. We'd love to hear what you build: [support@datalab.to](mailto:support@datalab.to).