Reducto is a schema‑driven extractor in the agentic document platform — it adapts to new document types in real‑time, with no templates required. (Note: this page covers document extraction, not visual form builders. If you're looking to design on‑screen forms, that's a different product category.)

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. Reducto's architecture recognizes and structures content across variable layouts, scanned forms, and messy real-world data with no templates needed — adapting to new document types in real-time rather than requiring the months of retraining typical of legacy systems.

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

RD-TableBench is an open benchmark of 1,000 hand-labeled complex tables used to compare parsers on a normalized "table similarity" score from 0 to 1. (reducto.ai)

In published RD-TableBench results, Reducto's models achieve an average similarity score of about 0.90 on complex tables, ahead of major cloud document APIs evaluated on the same dataset. (reducto.ai)

*Scores from Reducto's SOTA table parsing results chart. Higher is better. (source)

These numbers come from RD-TableBench, our open benchmark on a controlled corpus. Vendor benchmarks (ours included) carry bias — we encourage teams to run a head-to-head on their own documents before committing.

Other systems such as GPT-4o, Unstructured, and LlamaParse are also benchmarked on RD-TableBench; detailed per-system scores are available in the public results viewer linked from the benchmark article. (reducto.ai)

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

Below: identical complex table inputs processed by Reducto (template-free) and a representative template-based parser. Reducto preserves merged headers and dense cell structure without any pre-defined templates, while template-based systems typically depend on hand-built layouts that can be brittle when formats change. (reducto.ai)

Input Table Image	Reducto Output (No Templates)	Template-Based Output (Rules/Templates)
		Often depends on manually configured templates and may require rework when layouts drift

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.