ModelRefs / Vision-Language Stack — Architecture Pattern
Vision-Language Stack — Architecture Pattern
Image + text input pipeline with OCR, vision encoder, VLM, and grounded structured output.
Overview
Accept images alongside text, normalize and OCR, route to a vision-language model, and emit grounded structured output with bounding boxes when relevant.
When to use it: You need to reason over screenshots, documents, photos, or UI captures.
Pattern details
| Pattern class | multimodal |
|---|---|
| Difficulty | advanced |
| Topology | pipeline |
| Also known as | vlm pipeline, image+text llm |
| Last reviewed | 2026-06-07 |
Known failure modes
- OCR loss — Important text dropped during OCR. Mitigation: Run dual-path OCR + VLM and reconcile.
When not to use it
- Sending raw uncompressed images at full resolution.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Vision-Language Stack — Architecture Pattern.
Frequently asked questions
When should I adopt the Vision-Language Stack?
You need to reason over screenshots, documents, photos, or UI captures.
What are common failure modes of Vision-Language Stack?
OCR loss
Is Vision-Language Stack production-ready?
Yes when paired with the safety controls and observability hooks documented on the pattern page.