Polimill
Public AI infrastructure in Japan
OpenAI
Government/Public Service
Embedded deployment
Standard case | Useful reference with remaining gaps
Evidence level B
Deployment in progress/scaling
B
Evidence level
Polimill: Public AI Infrastructure in Japan
Evidence level measures whether a source can be located and reviewed; it does not mean vendor-reported claims were independently audited.
Standard case | Useful reference with remaining gaps
7 / 12
Business context1 / 2
Transformation workflow / 2
Technical workflow2 / 2
Human roles & governance1 / 2
Measured outcomes2 / 2
Source traceability1 / 2
Remaining gaps: Business context, Transformation workflow, Human roles & governance, Source traceability
Business problem
Local governments need to share expert experience while meeting public sector governance and sustainable operations.
Solution
Accompanied by OpenAI to build public AI infrastructure and knowledge capacity for reuse.
Technical architecture & production workflow
Step 01
SOP / History Case / Expert Interview
→
Step 02
Document Parsing, Cutting and Metadata Tags
→
Step 03
Embedding / semantic index
→
Step 04
Retrieving similar cases and rules based on current questions
→
Step 05
LLM is evidence-based advice and attachment
→
Step 06
• Rewrite the knowledge base of the new experience
Key technology & infrastructure components
Knowledge base/RAGEmbedding/vector searchPermissions and metadataLLMExpert review
Human roles & accountability
Government staff and experts are responsible for policy, facts and final decision-making.
FDE delivery actions
- "When will the staff come to see the teacher?"
- Interviews with experts to convert tacit judgment into searchable cases and rules
- Design knowledge particles, labels, versions and privileges instead of simply uploading documents
- Recall rate/Application of answers using real questions
- Keep feeding back feedback, wrong answers and new cases.
Reusable delivery patterns
- HF, high-cost, verifiable narrow-flow selection
- Steps that can be validated with a certainty tool to prevent model self-assessment
- Retain manual responsibility for high-risk actions
- For each manual amendment to follow-up searchable context/rules
Business outcomes & delivery results
In August 2026, the case was made public; the focus was on transforming the tacit knowledge of experts into a cross-autonomous reusable asset.
Evidence boundaries & verification notes
- Public information confirming business processes; technical components are abstract architecture based on public description
- The current link is the official aggregation entrance, and a deep link or page number that directly locates the case has yet to be added.