Labelbox Now Powers Multi-Modal, Multilingual & Code-Aware AI Workflows — With LLM-as-a-Judge
Hey Labelbox Community! 
AI is evolving rapidly — from multi-modal foundation models to LLM-powered evaluations, and now even into code generation and reasoning. Labelbox is here to help you meet the moment.
With expanded support for multi-modal data, multilingual tasks, and LLM-as-a-Judge, the platform is purpose-built for teams developing the next wave of intelligent systems — such as code-generating and code-editing agents.
Here’s what’s new and what makes Labelbox a cutting-edge solution for modern AI teams:
Multi-Modal Capabilities (MMC): Label Real-World, Complex Data
Modern models need to understand across text, images, audio, and structured data. Labelbox enables this by supporting true multi-modal workflows.
What’s Possible:
Image + Text (e.g., captioning, grounding, VQA)
Document + Audio (e.g., spoken document understanding)
Video + Metadata
Structured + Natural Language Inputs
Custom, nested ontologies to model complex relationships across modalities
Curate with semantic search, metadata filters, and model embeddings
Perfect for training multi-modal foundation models, fine-tuning vision-language models, and managing complex annotation pipelines.
Multilingual & Cross-Lingual AI Development
Labelbox now supports a multitude of human languages, enabling development of AI systems for global deployment.
Highlights:
Label and evaluate data in dozens of languages (from English and Spanish to Japanese, Arabic, and Hindi)
Language-specific prompt templates for LLM evaluation
Build cross-lingual datasets for translation, multilingual QA, and more
Use LLM-as-a-Judge to assess output fluency, accuracy, and cultural nuance in any supported language
Whether you’re working on global chatbots, LLMs for underserved languages, or multilingual retrieval systems, Labelbox is ready.
Code-Aware Annotation & Evaluation Workflows
With the rise of code-generating LLMs, Labelbox adds native support for programming-language data workflows.
Capabilities:
- Label and curate code in languages like Python, JavaScript, Java, C++, and more
Evaluate generated code using LLM-as-a-Judge
Tasks like:
- Code generation
- Code completion
- Code editing/fixing
- Code translation
- Functional code review
Customize LLM evaluation prompts to score correctness, readability, docstring quality, test coverage, etc.
This is ideal for building datasets for code LLMs, auto-coding agents, developer copilots, and more.
LLM-as-a-Judge: Smart Evaluation at Scale
LLM-as-a-Judge is one of the most powerful features in Labelbox — enabling automated, reliable evaluation of AI model outputs across use cases.
Supported Evaluation Types:
Summarization (faithfulness, brevity, style)- Instruction following (correctness, helpfulness)
- Multilingual output evaluation
- Multi-modal generation (image captions, audio descriptions)
- Code correctness and explanation clarity
- Safety & bias checks (toxicity, hallucinations, bias detection)
All evaluations are customizable, scalable, and embeddable within your labeling pipelines.
Built for Advanced LLM Training & Evaluation Workflows
Labelbox now supports the most critical workflows for LLM and agent development:
Reinforcement Learning with Human Feedback (RLHF)- Supervised Fine-Tuning (SFT)
Multimodal LLM Evaluation- Preference Ranking
LLM Chat Arena
Red Teaming & Safety Audits
Text-to-Image, Video, and Audio Tasks- Coding and AI Agent Tasks
These workflows are backed by integrated model evaluation, human feedback, and flexible APIs — making it easy to run robust experiments and accelerate iteration.
Fully Integrated with Your ML Stack
Labelbox ties all these capabilities into a cohesive, production-ready platform:
Catalog: Semantic data search & curation
Label Editor: Multi-modal, multi-language, and code-aware interfaces- Model: Pre-labeling and auto-evaluation
- Python SDK & APIs: Automate workflows, track progress, trigger reviews
From data collection to model validation, Labelbox supports you every step of the way.
Build the Next Generation of AI with Labelbox
Whether you’re fine-tuning a multi-modal LLM, deploying a multilingual chatbot, or building a code-first dev assistant, Labelbox gives you the tools to:
- Curate the right data
- Label it with precision
- Evaluate with scale
- Improve continuously
What are you building? Drop a comment or question below. Let’s push the frontier of AI — together. 