Introduction
In 2025, GenAI is no longer limited to just words on a screen.
From images to text, audio to documents, multi-modal models are now shaping how we interact with AI-powered applications.
So, where does AWS stand in this multi-modal future?
Let’s explore what’s possible right now on AWS when it comes to multi-modal GenAI and how to build with it.
What Are Multi-Modal Models?
Multi-modal models can accept or generate multiple types of data, such as:
- Text
- Images
- Audio
- Video
- PDFs or structured documents
The goal?
Enable richer, more natural input-output flows in AI apps.
Multi-Modal Options on AWS (2025)
| Capability | AWS Service / Integration |
|---|---|
| Text + PDF Understanding | Amazon Textract + Bedrock (RAG) |
| Text-to-Image Generation | Amazon Titan Image Generator (Preview), Stability.AI via SageMaker |
| Text + Image Q&A | Anthropic Claude 3 (via Bedrock, limited preview) |
| Visual Search / Image | Embeddings SageMaker + CLIP or ViT models |
| Speech-to-Text | Amazon Transcribe |
| Text-to-Speech | Amazon Polly |
| Multi-modal Fine-tuning | SageMaker Training Jobs with HuggingFace libraries |
AWS doesn’t have one multi-modal API, but you can combine services to build your own pipeline.
Example: Building a Document Q&A Assistant with Multi-Modal Input
Goal: Let users upload a scanned PDF and ask questions about it.
Architecture:
- User uploads scanned PDF → stored in S3
- Text extracted using Amazon Textract
- Text chunked + embedded using Titan Embeddings
- Chunks stored in OpenSearch
- User asks a question via UI → Bedrock (Claude or Titan) retrieves context → responds
- Response delivered in UI (or via Amazon Polly as voice)
- Text → Image → Vector → Response
- Entirely on AWS
Other Multi-Modal Use Case Ideas
| Use Case | AWS Stack |
|---|---|
| AI Form-Filling Agent | Textract + Lambda + Bedrock |
| AI Product Designer | Titan Image Generator + SageMaker Studio |
| Voice-Controlled FAQ Assistant | Transcribe + Lex + Bedrock |
| Visual Search Engine | SageMaker + ViT embeddings + OpenSearch |
| Contract Review Bot (PDF → Summary) | S3 + Textract + Bedrock + Guardrails |
Current Limitations
- Claude 3’s image input support is limited in Bedrock preview
- Titan Image Generator is still in preview with basic capabilities
- AWS does not offer one-click video or audio processing LLMs yet
- Some multi-modal models (like Gemini or GPT-4V) are not natively available on AWS
But with SageMaker + HuggingFace, you can self-host open multi-modal models.
Tools to Explore
- Amazon Bedrock Agents – for orchestrating input/output chaining
- Textract + AnalyzeDocument – for tables, forms, and OCR
- HuggingFace CLIP models on SageMaker – for image-text alignment
- Amazon Rekognition – for object and scene detection in images
- AWS Step Functions – to sequence multi-modal flows
Conclusion
AWS isn’t offering “GPT-4 Vision” yet—but you can build your own multi-modal systems by combining best-of-breed services.
The key isn’t one tool, it’s orchestration.
Use AWS services like Bedrock, Textract, Polly, OpenSearch, and SageMaker together to deliver intelligent, multi-sensory applications today.
