Capabilities
From understanding language to writing code, from seeing the world to acting in it — these are the pillars of modern machine intelligence.
Live agent
Watch an AI agent think in real time.
Conversation & comprehension
Natural Language
Models that read, write, summarize, translate, and converse across hundreds of languages.
From chatbots to research assistants, language models understand context, nuance, and intent at human-level fidelity.
Perception & recognition
Computer Vision
Systems that see — classifying, detecting, segmenting, and understanding visual content.
Vision models read images, video, and spatial data like a second nervous system for software.
Software at the speed of thought
Code Generation
AI that writes, tests, refactors, and explains code across dozens of languages and frameworks.
Coding agents go beyond autocomplete — they plan architectures, fix bugs, and ship features from a single prompt.
Imagination engines
Creative Synthesis
Generative models that produce art, music, video, design, and brand systems from intent.
A sentence becomes a symphony. A sketch becomes a film. The creative field expands beyond what any individual could produce alone.
Goal-directed action
Autonomous Agents
AI systems that plan, use tools, navigate interfaces, and execute complex workflows end to end.
Agents decompose goals into steps, call APIs, browse the web, manage files, and adapt when things go wrong.
Forecasting & optimization
Predictive Intelligence
Models that anticipate outcomes, model scenarios, and find optimal paths through complex systems.
From supply chains to healthcare, predictive AI turns historical data into forward-looking decisions.
These capabilities are not islands — they are interconnected layersthat compound each other's power. Vision feeds language. Language feeds code. Code feeds agents. Agents feed back into learning. The result is a system greater than the sum of its parts.