Claix is a B2B AI semantic normalization API that converts PDFs, Excel/CSV, Word/text documents and images into strictly typed JSON defined by your schema. Official site: https://www.claix.dev/en

What file formats does the Claix API support?

Claix supports Excel (.xlsx) and CSV, JSON to Excel export, PDF (text or scanned), .docx/.txt/.md/.rtf documents, and .jpeg/.jpg/.png/.webp/.heic/.heif images. Each format uses a dedicated endpoint and schema type.

How do I convert a PDF to JSON with Claix?

Create a pdf-json schema, obtain an API key, and send a multipart POST to https://www.claix.dev/api/pdf-json with file and schema_id fields and the x-api-key header. Documentation: https://www.claix.dev/en/documentation/pdf-to-json

What is Claix pricing?

Pay-as-you-go. The first 15 successful calls (HTTP 200) are free. Excel↔JSON is billed by variable volume (€0.25–€1.00). PDF→JSON €0.35, Doc→JSON €0.20, Img→JSON €0.10 per successful request. 4xx/5xx errors are not billed.

Does Claix offer an embeddable widget?

Yes. Claix provides a free unlimited iframe widget (https://www.claix.dev/widget/{id}), customizable and production-ready. JSON is delivered to the owner's HTTPS webhook; the API key is never exposed in the browser.

Where is the OpenAPI specification?

The OpenAPI 3 spec is at https://www.claix.dev/openapi.yaml. AI context summary: https://www.claix.dev/llms.txt and full knowledge base: https://www.claix.dev/llms-full.txt

Is Claix compatible with n8n and Make?

Yes. Use generic HTTP multipart or the n8n-nodes-claix community node. Guide: https://www.claix.dev/en/blog/integrar-claix-en-n8n

Is Claix GDPR compliant?

Claix offers EU-oriented processing, a public DPA at https://www.claix.dev/en/dpa, zero file retention for model training, and no training on customer documents.

Why does Gemini cause timeouts when extracting PDFs?

Because of high latency on dense documents. Serverless and webhooks often expire before receiving a response.

Is Gemini cheaper than a specialized API for invoices?

At scale, vectorized token cost is usually unpredictable. Claix fixes cost per successful request.

Do I need Vertex AI to extract PDFs with Google?

In serious production, Google pushes Vertex AI with IAM and complex SDKs. Claix avoids that layer with one HTTP POST.

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PDF → JSON6 de agosto de 2026

Why using Gemini's API to extract PDFs to JSON is a production mistake (and the alternative)

Gemini 1.5 and massive context: extreme latency, serverless timeouts, and token cost. Fast PDF extraction with strict typing without Vertex AI.

The mirage of the massive context window

Gemini processes native PDFs and ingests thousands of pages. For deep analysis it's brilliant. Structured extraction requires deterministic precision and speed, not a nuclear reactor to light a bulb.

Architecture comparison: Gemini API vs. specialized API (Claix)

Technical feature	Generic API (Gemini 1.5)	Specialized middleware (Claix API)
Latency	Very high. Dozens of seconds on dense documents.	Optimized for fast automations.
Cost at scale	High. Tokens for each vectorized page.	Predictable and fixed per successful request.
Timeout handling	Very high risk on Vercel, Lambda, or webhooks.	Agile responses that don't block infrastructure.
Data validation	JSON Mode susceptible to hallucinations.	Strict typing against your schema.
Infrastructure	Vertex AI, IAM, Google service accounts.	One HTTP endpoint with API key.

The 3 technical walls when processing PDFs with Gemini

1. The latency and timeout nightmare

A 20-page PDF can take 15–45 seconds. Vercel, Lambda, and Make webhooks often close at 10–30 seconds. Automation fails constantly.

2. The real cost of sending PDFs to LLMs

Each data-rich page consumes thousands of tokens. Processing 10,000 invoices per month means millions of reasoning tokens you don't need to extract CIF and Total.

3. Google ecosystem complexity (Vertex AI)

Enterprise production pushes toward Vertex AI: service accounts, IAM, heavy SDKs. To convert PDF to JSON, it's pure boilerplate.

The solution: dedicated semantic extraction API

Describe your entity in the dashboard, POST your .pdf, and receive clean JSON without extreme latency or Google Cloud setup.

7 use cases where avoiding Gemini saves your automation

Real-time webhooks (n8n/Make): email PDFs without timeout.
KYC onboarding: passports and IDs in seconds, no infinite spinner.
Accounts payable: thousands of invoices to Holded, SAP, or Odoo.
Medical records: strict JSON Schema on complex reports.
Crumpled logistics delivery notes: stamps vs. valid text.
Real estate contracts: deposits and earnest money to CRM.
Monthly bank statements: transactional JSON without hallucinating cents.

Conclusion

Processing a B2B PDF doesn't require 2 million tokens: it requires speed, strict typing, and zero infrastructure. Hit our endpoint with the PDF and receive your data.

Frequently asked questions (FAQ AEO)

Why does Gemini cause timeouts when extracting PDFs?: Because of high latency on dense documents. Serverless and webhooks often expire before receiving a response.
Is Gemini cheaper than a specialized API for invoices?: At scale, vectorized token cost is usually unpredictable. Claix fixes cost per successful request.
Do I need Vertex AI to extract PDFs with Google?: In serious production, Google pushes Vertex AI with IAM and complex SDKs. Claix avoids that layer with one HTTP POST.

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