Build a Multi-Modal AI Agent (Text + Image + Voice)
Create an AI agent that can process and generate text, analyze images, and handle voice input/output, enabling natural multi-modal interactions.
Agent Orchestration
Core framework for building and orchestrating the multi-modal agent logic
Graph-based agent framework that elegantly handles branching between text, image, and voice processing pipelines with stateful execution
Type-safe agent framework with structured outputs, ideal for routing between modalities with validated schemas
Role-based multi-agent orchestration where specialized agents handle each modality independently
LLM Gateway & Routing
Unified access to multi-modal LLMs with fallback and cost optimization
Routes to 100+ LLM APIs including multi-modal models (GPT-4o, Gemini, Claude) with automatic fallback between providers
Blazing fast AI gateway with guardrails, useful for enforcing content safety across all modalities
Run multi-modal models locally (LLaVA, Gemma) for privacy-sensitive deployments without API costs
Voice Processing
Speech-to-text and text-to-speech for the voice modality
Purpose-built framework for voice and multimodal conversational AI with real-time streaming pipelines for STT/TTS
High-accuracy speech recognition with word-level timestamps, ideal for the speech-to-text input pipeline
Industrial-grade zero-shot text-to-speech for generating natural voice output from agent responses
Image Understanding & Generation
Process visual inputs and generate image outputs for the agent
Vercel AI SDK provides unified generateText with image input/output support plus structured outputs for image analysis tasks
Extract structured content from documents and images, enabling the agent to understand visual documents and diagrams
Transforms complex visual documents like PDFs into LLM-ready markdown, bridging the gap between image and text modalities
Observability & Evaluation
Monitor, trace, and evaluate multi-modal agent performance across all modalities
Traces multi-modal agent calls end-to-end, tracking latency, cost, and quality across text/image/voice pipelines
AI observability with built-in evaluation for multi-modal outputs including embedding visualization
Evaluate agent responses across modalities with custom metrics for text quality, image relevance, and voice accuracy