parso
PDF → RAG Pipeline Solution

PDFs break your RAG

Extract them perfectly. One function. 99.9% accuracy.

Complex PDF

Tables, forms

❌

broken

Parso

2 sec

⚡

perfect

Clean JSON

RAG-ready

✓
Try itLive demo
CodePython
from parso import extract

# One line
data = extract("document.pdf")

# Perfect JSON for RAG
print(data.tables)  # ✓
The Problem

The extraction difference

Same PDF. Different results. Critical for RAG.

Without Parso

PDF → Extraction

Revenue Q3 $45.2M
undefined NaN
[lost data]

RAG Output

"No data found"

With Parso

Recommended

PDF → Extraction

{
  "Q3": 45200000,
  "growth": 0.23
}

RAG Output

"$45.2M, up 23%"

Structured data = Accurate RAG
Core Features

Handles your documents

Financial & legal PDFs extracted perfectly

Financial reports

99.9%

10-K, 10-Q, earnings

Legal contracts

99.7%

NDAs, MSAs, employment

Bank statements

99.8%

Transaction data, balances

Court documents

99.6%

Filings, judgments, briefs

Tax filings

99.9%

1099s, W-2s, returns

SEC filings

99.8%

S-1, 8-K, proxy statements

Technical capabilities

Complex tables

Multi-page, nested, merged cells

Multi-column

Preserves reading order

Scanned PDFs

Built-in OCR processing

200+ pages

Stream large documents

Form fields

Extract filled values

Validation

Automatic accuracy checks

Any PDF → Perfect JSON

If it's a document, we extract it accurately

Integration

Your RAG pipeline. One line better.

No migrations. No rewrites. Just add Parso to what you have.

×

Without Parso

PDFs break your embeddings
Tables become gibberish
RAG returns wrong answers

With Parso

Perfect extraction every time
Tables stay structured
RAG accuracy jumps to 99%
your_pipeline.py
# Before: Complex parsing logic
pdf = PDFParser(file)
text = clean_text(pdf.extract())
tables = fix_tables(pdf.tables)
chunks = custom_chunker(text)
# After: Just Parso
from parso import extract
data = extract(file)
# Perfect data, ready to use
vectordb.insert(data.chunks)
Ready to run
Instant
1 line
of code change
2 min
integration time
99%
extraction accuracy

Works with your stack

Copy & paste ready
$pip install parso
example.py
from parso import extract

# That's it. Really.
data = extract("complex_financial.pdf")

# Perfect extraction, ready to use
print(data.tables[0])     # ✓ Structured tables
print(data.metadata)      # ✓ Document info
print(data.chunks)        # ✓ RAG-ready chunks

Ready to integrate?

Get your API key and start extracting in 2 minutes

Built for production RAG

Real metrics from real deployments

2s

Avg extraction

$0.001

Per page

99.9%

Accuracy

10x

Faster than others

Processing speed reality check

Parso
2s
Unstructured
12s
Reducto
18s
Document AI
24s

Benchmark: 10-page financial statement with complex tables

Streaming API

Process 500-page docs without waiting. Stream results as they're ready.

Validation included

Every extraction validated. Know exactly what worked and what didn't.

Type preservation

Numbers stay numbers. Dates stay dates. No post-processing needed.

Why RAG pipelines fail

Bad data in = hallucinations out

Why Parso works

Perfect data in = accurate responses

Success Stories

See The Difference

Real PDF extraction problems visualized

Financial Tables

Quarterly data extraction

Original PDF
Q1
Q2
Q3
$1.2M
$1.5M
$1.8M
Typical Parser
Q1Q2Q3$1.2M$1.5M
$1.8M
Parso Result
{
"Q1": "$1.2M",
"Q2": "$1.5M",
"Q3": "$1.8M"
}

Legal Documents

Contract hierarchy

Original PDF
1. Terms
1.1 Payment
30 days
1.2 Delivery
5 days
Typical Parser
1.Terms1.1Payment
30days1.2Delivery
5days
Parso Result
{
"sections": {
"1.1": "30 days",
"1.2": "5 days"
}
}

Multi-Column PDFs

Two-column layout

Original PDF
Asset: $5M
Debt: $2M
Revenue: $8M
Cost: $3M
Typical Parser
Asset:$5MRevenue:
$8MDebt:$2M
Cost:$3M
Parso Result
{
"Asset": "$5M",
"Debt": "$2M",
"Revenue": "$8M",
"Cost": "$3M"
}

Performance Gains

Actual Metrics
10-K Extract
3 days30s
8,640×
Contract Parse
6 hours12s
1,800×
SEC Process
2 days2min
1,440×

Stop fighting with PDF parsers. Get structured data instantly.

Pricing

Pricing that makes sense

Start free. Scale without breaking the bank.

Free

$0/mo

Perfect for trying out and small projects

10,000 pages/mo
All extraction features
API access
Community support
Most Popular

Pro

$49/mo
Save $1,951/mo vs competitors

For production RAG systems

100,000 pages/mo
Priority processing
Email support
Webhook callbacks

Enterprise

$0.0008/page
25x cheaper than alternatives

Volume pricing for scale

Unlimited pages
Dedicated support
Custom integrations
SLA guarantees
25x

Cheaper than Document AI

10x

Faster than competitors

99.9%

Accuracy on financial docs

Calculate your savings

10,000 pages
1k500k

Competitors

$200

$0.02/page

Your monthly cost

$0

Free tier

You save

$200

per month

No setup fees • No contracts • Cancel anytime

Start extracting in 2 minutes

Join thousands of developers who stopped fighting with PDFs

Free tier • No credit card • Cancel anytime

10,000 free pages/mo
2-min setup
$0.001/page after

Quick Start Guide

1

Install

pip install parso
2

Import

from parso import extract

Extract

data = extract("doc.pdf")

Try the API

Test with your PDFs right now

See Examples

Real PDFs, real extractions

Trusted by developers at

YC StartupsSeries B FintechsFortune 500