From model to business outcome.
A practical taxonomy for understanding who builds each layer of the enterprise AI stack and how those layers connect.
Foundation models
Companies building language, multimodal, reasoning, image and open-weight foundation models.
Cloud & compute
Cloud platforms, GPU capacity and enterprise infrastructure for training and running AI.
Inference platforms
Managed inference, model serving, acceleration and deployment infrastructure.
Data & vector
Lakehouses, databases, vector search and knowledge graph infrastructure for AI systems.
MLOps & observability
Experiment tracking, evaluation, monitoring, tracing, governance and model operations.
Agents & automation
Frameworks and platforms for building, orchestrating and operating AI agents.
Developer tools
AI coding assistants, app builders, code review and software engineering platforms.
Search & knowledge
Enterprise search, web retrieval, answer engines and RAG infrastructure.
Enterprise applications
AI assistants embedded across productivity, CRM, service management and business software.
Customer experience
Conversational support, contact center automation and customer-facing AI agents.
Creative media
Image, video, voice, music and design platforms powered by generative AI.
3D & spatial AI
Text-to-3D, image-to-3D, world models, digital twins and AI-native spatial content creation.
AI video & filmmaking
Video foundation models, virtual production, cinematic generation and AI-assisted filmmaking workflows.
Security & governance
AI security, model risk, guardrails, compliance and responsible AI platforms.
Robotics & autonomy
Autonomous vehicles, humanoid robots and physical intelligence platforms.
Industry AI
Purpose-built AI platforms for healthcare, legal, finance and other regulated industries.