Unverified50% confidenceOpinionExact time
The current AI technology stack typically includes a data storage layer, a model layer, and an application layer, but often lacks an intermediate layer between data and model that carries business semantics.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/21/2026
First Seen
Valid until: 12/20/2026
Sources
Related Entities
Related Claims
Unverified企业级AI平台通常分为基础模型层、API抽象层、编排层和治理层四个核心层次77% similarUnverifiedAI产品的用户分层运营通常体现为阶梯式架构：免费层提供有限额度、专业层提供更高速率限制和SLA、企业层提供私有化部署和定制微调77% similarUnverifiedIn enterprise AI deployment, data silos are often a bigger bottleneck than model capability, as many companies' data is locked in local databases and internal APIs.76% similarUnverifiedThe topmost layer of the AI industry's hierarchical structure is the foundation model layer (e.g., the GPT series, LLaMA, DeepSeek), the middle layer is the framework and middleware layer (e.g., LangChain, vector databases), and the bottom layer is the application development layer, analogous to the IaaS-PaaS-SaaS architecture of the internet era.74% similarUnverifiedA local AI inference stack can be broken down into five layers: model format and quantization, execution runtime and compute kernels, serving engine and scheduler, local daemon and model lifecycle management, and application workbench.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/939678API
curl https://kongchang.com/api/v1/knowledge/claims/939678MCP
get_claim(id=939678)