Struktur vs Unstract

Unstract and Struktur are both open source tools for structured data extraction. Unstract offers a visual prompt engineering interface and n8n integration. Struktur focuses on an autonomous agent approach and CLI-first workflow.

Quick Comparison

Unstract Overview

Unstract is an open source document processing platform with both a self-hosted edition and cloud offering. It emphasizes visual prompt engineering and workflow automation.

Key Features

Prompt Studio — Visual interface for designing extraction prompts. See how prompts perform, iterate without code changes.

LLMChallenge — Uses two LLMs: one extracts, one challenges. Either get the right answer or NULL (no wrong answers). Available in cloud/on-prem, not open source edition.

SummarizedExtraction — Summarizes document sections before extraction, reducing token usage up to 6x.

SinglePass Extraction — Combines all prompts into one, reducing token usage up to 8x.

n8n Integration — Connect extraction to 400+ integrations via n8n workflows.

Open Source Edition Limitations

The open source edition lacks:

• SSO support
• Human quality review
• LLMChallenge verification
• SummarizedExtraction
• SinglePass Extraction

These features require cloud or on-prem licenses.

Deployment

Unstract requires Docker Compose with multiple containers:

• PostgreSQL with PGVector
• Unstructured.io for parsing
• Ollama for local LLMs
• Unstract platform

Minimum 8GB RAM recommended.

Struktur Overview

Struktur is a lightweight extraction library and CLI. It provides multiple extraction strategies including an autonomous agent that explores documents without predefined prompts.

Key Features

Autonomous Agent — LLM explores documents using tools (read, grep, find), decides what to extract dynamically.

Multiple Strategies — Simple, parallel, sequential, agent, double-pass. Choose based on document type.

Schema-aware Auto-merge — Automatically deduplicates and merges array results.

CLI-first — Extract from command line without writing code.

Lightweight — Single npm package, no Docker required.

Deployment

Install via npm/bun:

npm install @struktur/sdk
# or
bun add @struktur/sdk

Or use CLI:

npx struktur extract invoice.pdf --schema schema.json

No infrastructure required beyond an LLM API key.

Approach Differences

Prompt-based (Unstract)

1. Design prompts for each field in Prompt Studio
2. Test prompts against sample documents
3. Deploy prompts to production
4. Documents processed through fixed prompt pipeline

Works well when:

• Document structure is known
• You want visual iteration
• Non-technical users design extractions

Agent-based (Struktur)

1. Define output schema
2. Agent explores document, decides what to read
3. Agent extracts iteratively
4. Output validated against schema

Works well when:

• Document structure varies
• You don't know what sections matter
• You want adaptive extraction

Verification Differences

Schema Validation (Struktur)

Struktur validates output against JSON Schema. If validation fails, it sends errors back to the LLM for retry. Most extractions converge in 2-3 attempts.

LLMChallenge (Unstract)

Unstract's LLMChallenge uses two LLMs:

1. Extractor LLM produces output
2. Challenger LLM verifies correctness
3. If challenger disagrees, return NULL instead of wrong answer

This prevents hallucinations but doubles token costs. Not available in open source edition.

Cost Optimization

Struktur

• Choose cheaper models (GPT-4o-mini, local LLMs)
• Use parallel strategy for speed
• Use simple strategy for small documents
• Agent only explores relevant sections

Unstract

• SummarizedExtraction reduces tokens 6x
• SinglePass reduces tokens 8x
• Both require cloud/on-prem license

When to Choose Struktur

• Want autonomous agent — Documents explore themselves
• Prefer CLI-first workflow — Extract without writing code
• Lightweight self-hosting — No Docker stack required
• TypeScript/JavaScript stack — Native SDK
• Variable document structures — Agent adapts
• Full open source features — No feature-gated capabilities

When to Choose Unstract

• Need visual prompt engineering — Prompt Studio for iteration
• Want LLMChallenge verification — Dual-LLM validation
• Using n8n workflows — Native integration
• Python-centric stack — Python SDK
• Non-technical users — Visual interface
• Enterprise features — SSO, human review (cloud/on-prem)

Integration Comparison

Struktur

import { extract } from '@struktur/sdk';

const result = await extract({
  artifacts: [{ path: 'invoice.pdf' }],
  schema: invoiceSchema,
  strategy: 'agent',
});

console.log(result.data);

Unstract

from unstract.sdk import UnstractSDK

client = UnstractSDK(api_key="...")
result = client.extract(
    document="invoice.pdf",
    schema=invoice_schema,
    prompt_profile="invoice_extraction"
)

Architecture Comparison

Migration Path

Both use JSON Schema for output definitions. Schemas are portable between platforms.

From Unstract to Struktur:

1. Export schema from Unstract
2. Use directly in Struktur (compatible format)
3. Replace prompt profiles with strategy selection
4. Deploy without Docker stack

From Struktur to Unstract:

1. Use same schema
2. Create prompt profile in Prompt Studio
3. Deploy via Docker Compose

See Also

• Struktur vs LlamaIndex — Cloud vs self-hosted
• Struktur vs Instructor — Full pipeline vs library
• What is an Extraction Agent?