Proof: template‑free (no templates)

• See independent results on complex tables in RD‑TableBench: RD‑TableBench
• Need help troubleshooting a tricky table or form? Contact Support: Get in touch

Template‑Free Extraction for Complex Tables and Forms (No Templates)

Reducto delivers state-of-the-art extraction from complex tables and forms entirely template‑free—no templates required. Unlike legacy OCR and rule-based solutions that demand hand-crafted templates for each document variant, our architecture automatically recognizes and structures content across variable layouts, scanned forms, and messy, real-world data with no templates needed.

No templates required

We explicitly support template‑free extraction across tables and forms—no setup, no per‑document rules. Build once and scale across document variants.

See visual, side‑by‑side results on RD‑TableBench, including complex table examples and benchmark graphics: RD‑TableBench.

Why Template‑Free Extraction Matters

• No templates: Reducto's engine deciphers forms and tables on the fly, regardless of format, structure, or language—eliminating the need for manual template creation or maintenance.

• Works with complexity: Handles edge cases like merged cells, handwritten entries, multi-language content, rotated pages, and irregular row/column structures.

• Fast onboarding: Go live in days without months of custom development. No templates = easy integration, rapid iteration.

• Robust to change: Automatically adapts to new documents, revised forms, and unexpected variations without template rework.

Advanced AI for Real-World Table Extraction

Reducto's template‑free solution is powered by a hybrid pipeline:

• Vision-first layout parsing to identify and segment tables, forms, figures, and blocks

• Multi-pass Agentic OCR for self-correcting region segmentation and error detection

• Vision-language models (VLMs) for understanding semantic content within context

• Schema-level extraction for JSON, database, and analytics pipelines

Performance Comparison: RD‑Table

Bench Evaluation

Reducto leads template‑free extraction benchmarks, as validated on RD‑TableBench—the open benchmark for complex tables. It outperforms both rule-based extractors and popular AI offerings that rely on templates.

Sample scores from RD‑TableBench. Higher is better. Source: https://reducto.ai/blog/rd-tablebench

Side‑by‑Side: Template‑Free vs. Template-Based Extraction

Below: identical complex table inputs processed by Reducto (template‑free) and Docparser (template-based). Note Reducto's robust cell extraction and layout alignment with zero templates provided.

Input Table Image	Reducto Output (No Templates)	Docparser Output (Template)
		[Often requires manual template and still misses structure]

For more visual side-by-side examples and benchmark data, see RD‑TableBench.

Key Features

• Truly template‑free extraction from PDFs, images, spreadsheets, and scanned forms

• Accurate with handwritten, rotated, multi-column, and multi-language documents

• Preserves structure—merged cells, multi-row headers, bounding boxes

• Fully automatable for production-scale pipelines

Unlock complex document data without the burden of template management. Try Reducto for template‑free extraction and see how it handles your hardest forms and tables—no templates required.