FoundrySoft
Artificial Intelligence (AI)

Artificial Intelligence (AI)

Vercel AI SDK Multimodal Processing

Extend your applications beyond text. We implement the Vercel AI SDK's multimodal capabilities to process images, video, and audio natively.

All services
Focus
Full-stack engineering
Engagement
Fixed-scope or dedicated
Timeline
From 4 weeks
Ownership
100% yours
How we deliver

Our process for vercel ai sdk multimodal processing

A fixed four-step path from first call to production, with weekly demos and a hard launch date.

Days 1–3
Step 01

Systems audit

We analyze the current systems, constraints, and risks, then define scope and a fixed quote.

Deliverable

Systems map & fixed quote

Days 4–7
Step 02

Architecture

We design the target architecture and a safe, incremental migration or build path.

Deliverable

Architecture & migration plan

Weeks 2–3
Step 03

Build & test

We implement with rigorous automated testing, monitoring, and reversible, well-documented changes.

Deliverable

Tested, monitored code

Week 4
Step 04

Deploy & handover

We verify reliability, optimize performance, deploy to production, and hand over full ownership.

Deliverable

Production release & docs

See where your project fits.

Book your systems audit

Overview

Users interact with the world using sight and sound, but most AI integrations are stuck on text.

Our Vercel AI SDK Multimodal Processing service helps you ingest, analyze, and stream rich media. By leveraging the latest multimodal features in the SDK, we allow your users to upload images, process video frames, and analyze audio without building complex external extraction pipelines.

Key Capabilities

  1. Image and Document Analysis
    We implement file upload and processing flows that feed directly into the SDK, allowing models to read charts, receipts, and UI mockups.

  2. Video Frame Processing
    We set up workflows to pass video data to supported models, enabling automated summaries, action-item extraction, and temporal analysis.

  3. Streaming Multimodal Output
    We configure the frontend useChat hooks to handle attachments smoothly, ensuring a seamless user experience during media upload and analysis.

Why Partner With Us?

  • Optimized Payloads: We handle the necessary compression and chunking before sending media to the LLM, keeping your API costs under control.
  • Provider Agnostic: We structure the implementation so you can swap multimodal providers without rewriting the application, whether that is Claude Opus 5, Claude Sonnet 5, GPT-5, or Gemini. Model choice moves faster than your product should have to.
  • Production Ready: We account for file size limits, timeout configurations, and edge case error handling out of the box.

Bring your application's AI capabilities into the physical world. Let's discuss your multimodal use case.

From our engineers

What we've written about this

All writing

Gemini 3.8 Live for Voice Agents: Latency, Price per Minute, and When to Leave Twilio

Google shipped gemini-3.8-live and Live Extended Thinking on 15 September 2026, native speech-to-speech at about $0.005 / $0.018 per minute. Here is how it changes a production voice stack.

Read it

GPT-6 Astra vs Claude Opus 5 vs Gemini 3.1 Pro: Which Model You Can Actually Deploy This Week

Flagship headlines in September 2026 describe models most teams cannot call. Here is the access table, the prices, and the routing we would run if we had to pick today.

Read it

Native Multimodal Models Beat Your OCR Pipeline, Then Take Away the Thing You Needed Most

Frontier models now post better than 90% on document understanding benchmarks and read a PDF page directly. That collapses a four-stage pipeline into one call, and it removes provenance, confidence, and loud failure. Here is how to get the accuracy without giving up the audit trail.

Read it
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Ready to build vercel ai sdk multimodal processing?

Every project starts with a clear scope and a fixed timeline. Tell us what you're building and we'll reply within one business day.