Why Roysa

Built on a foundation of trust and transparency

The Problem

Most document AI systems extract text without explaining where it came from.

Vision Language Models like GPT-5.2 and Gemini can read documents, but they treat extraction as a black box. They provide answers without showing where they found them — no coordinates, no visual proof, no way to verify.

Cannot locate data spatially on the page
No visual grounding or bounding boxes
May hallucinate or misread values
No built-in verification workflow
Our Approach

Every extracted value must be explainable, verifiable, and visually grounded.

Roysa is built around traceability. We don't just tell you what we found — we show you exactly where we found it, why we're confident, and how you can verify it yourself.

Key Principles

01

No Black-Box Extraction

Every extraction decision is transparent. See the reasoning, not just the result.

02

Evidence-First AI

Visual grounding means every value points back to its source on the document.

03

Designed for Review

Built from the ground up to support human verification and audit requirements.

04

Real-World Ready

Engineered to handle noisy scans, skewed images, and imperfect documents.

The Roysa Difference

VLMs (GPT-5.2, Gemini 3)
Roysa
Spatial Understanding
Cannot locate on page
Precise bounding boxes
Visual Grounding
Text output only
Shows exactly where data is
Hallucination Risk
May generate incorrect values
Grounded in document evidence
Verification
Manual re-check required
Built-in visual audit
Confidence
No location confidence
Granular confidence scores

See the Difference

Experience document AI built on transparency and trust.

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