// use cases · document extraction

Turn documents into
structured data.

Read claims, invoices, contracts and forms, text, tables and scans, and return clean JSON. On EU infrastructure, fully auditable.

book_a_call

// how it works

From messy documents to clean fields.

Vision, extraction and classification from a single OpenAI-compatible endpoint — at volume, and only inside the EU.

step 01

Read any document

gemma4

Parse PDFs, scans and forms — text, tables and layout, including images — with a vision-capable model. No OCR pipeline to maintain.

step 02

Extract to your schema

deepseek-v4-flash

Pull fields straight into your own JSON schema with structured outputs — every value where you expect it, every time, ready to validate.

step 03

Classify & route

qwen3-embedding

Classify the document type and route it to the right workflow, with embeddings you can audit — confident matches first, edge cases flagged.

// drop-in

Change one line. Keep your pipeline.

Vision input and structured outputs work the OpenAI way. Change the base URL and key, point at gemma4, and get your schema back — privately.

read_the_docs

extract.py

from openai import OpenAI

client = OpenAI(
    api_key="sk-...",
    base_url="https://api.helmcode.com/v1",  # one line changes
)

# vision in, structured JSON out — straight into your schema
result = client.chat.completions.create(
    model="gemma4",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Extract the invoice fields."},
            {"type": "image_url", "image_url": {"url": invoice_png}},
        ],
    }],
    response_format={"type": "json_schema", "json_schema": invoice_schema},
)

// why helmcode

Extraction you can put in production.

The documents you process are full of PII and money. Closed APIs ask you to upload all of it — and log it.

Zero logs, by architecture.

The documents you extract — and the data inside them — are never stored, and never train a model.

Processed in the EU.

Invoices, claims and contracts stay on EU infrastructure — not on US hyperscalers subject to the Cloud Act. GDPR and AI Act native.

Vision + JSON, one API.

Read a scan and return validated JSON from a single OpenAI-compatible endpoint — no separate OCR vendor, no glue code.

No caps at volume.

Process millions of documents a month. Limits are RPM and concurrency per key — never total tokens, so a busy month isn't a surprise bill.

Open models, your schema.

DeepSeek V4-Flash, Qwen 3.6, Gemma 4. Your fields, your JSON — no proprietary extraction format to lock you in.

Drops into your pipeline.

OpenAI-compatible structured outputs and vision. Change the base URL and key; your extraction code keeps working.

In production across

Banking & fintech
Insurance
B2B SaaS
Public sector
Energy & utilities
Manufacturing
Legal

In production at

// extraction faq

Extraction, answered.

What operations and engineering teams ask before automating document workflows.

Can it read scanned PDFs and images, not just digital text?

Yes. gemma4 is vision-capable (and mimo-v2.5 is fully multimodal), so it reads scans, photos and forms — text, tables and layout — without a separate OCR pipeline.

Can I get the output in my own schema?

Yes. Use OpenAI-compatible structured outputs (response_format json_schema) so fields land in your exact JSON shape — ready to validate and store.

Do you store the documents I send?

No. Zero logs — documents and the data extracted from them are never persisted and never train a model. Extraction stops being a privacy liability.

How do I trust the output?

Structured outputs constrain the response to your schema, so fields are always present and typed. Validate per field and flag low-confidence cases for review.

Can it handle high volume?

Yes. There are no token caps — limits are RPM and concurrency per API key — so you can process millions of documents a month on predictable, flat pricing.

What about highly sensitive documents?

Run on a dedicated GPU or fully on-premise inside your own datacenter — the same API and code, with documents that never leave your network.

// get started

START BURNING TOKENS

Skip the AI infra work. Deploy your first private inference endpoint today.

Flat rate. EU data. OpenAI API compatible.