Intelligence in software¶

For a software AI team, the scarce resource is often a repeatable customer problem, a reliable evaluation set and a lawful route to useful data. A model community helps when it supplies a concrete resource or a credible introduction.

Data, compute and models support an evaluated product connected to customers. — Fig. 3 An AI product connects models to a customer workflow.¶

Choose an entry point¶

For model engineering and developer connections, begin with Model Speed Space, Zhangjiang Model Community, Shanghai AI Laboratory resources or a relevant university group. For enterprise deployment, compare an operator’s actual buyer relationships with the industry requirements. For an independent founder, check the current Yangpu OPC community policy and Changning’s published carriers.

We treat foundation models, domain models, agents, multimodal systems, industrial software, evaluation, AI security and scientific software as different businesses. An accelerator that can introduce a manufacturer may not supply a regulated financial dataset or an inference contract.

In central and western districts, Jing’an’s Shibei Hi-Tech Park and Shutong Valley focus on big-data, blockchain and enterprise AI compliance; Huangpu pairs its five-year fintech clustering policy with the Entrepreneurship Companion mentor network; and Songjiang’s 2026 Data Elements Special Fund supports corpus governance and AI data-space applications.

Build the smallest credible pilot¶

Prepare one task, a baseline, a held-out evaluation set and a target metric. State cost per completed task, latency, error handling and human review. Name the data owner, deployment environment and accountable buyer. A pilot needs an owner, a budget, acceptance criteria and a path to a production contract.

Budget training, fine-tuning, inference, retrieval, storage, networking, annotation and evaluation separately. A compute reimbursement may exclude storage or networking. A model or corpus voucher may cover only an approved supplier and a specified historical cost period. Retain usage logs, invoices, contracts and payment records from the beginning.

Before public deployment¶

Define whether the service is an internal tool, a business-facing deployment or a public-facing generative service. Ask the relevant authority and a qualified adviser which model registration, algorithm filing, content labelling, data, sector and network requirements apply. Requirements attach to the actual service, not to an AI label on a pitch deck. This atlas supplies routing questions rather than an exhaustive legal procedure.

Evidence S114. 上海市经济信息化委关于组织2026年度上海市“模塑申城”工程相关补贴申报工作的通知.