OpenAI Public Sector Asia-Pacific & Oceania

Polimill

Document Processing · Enterprise Knowledge Search

Polimill needed to reduce administrative burden across fragmented Japanese municipal systems so public employees could find prior decisions, prepare assembly responses, and deliver services without each municipality building separate AI tools.

3-5x development speed increase from Codex and OpenAI hands-on support
About 1,050 municipalities across Japan using QommonsAI
About 550,000 public employees across Japan now use QommonsAI

Reported impact

Business outcome

Polimill created a common public-sector AI platform used across Japan, sped up its own product development, improved knowledge reuse across municipalities, and showed that less-experienced staff can draft stronger policy work with AI support.

  • Compliance
  • Productivity Improvement
  • Scalability

Solution

Polimill built QommonsAI as a shared generative AI foundation for municipal work in Japan. The platform started by standardizing assembly minutes and other administrative records that were previously scattered across municipalities, then applied AI to add metadata and create a searchable cross-municipality knowledge base. QommonsAI now supports workflows such as assembly response, public services, social welfare, and legal search for about 1,050 municipalities and roughly 550,000 public employees. OpenAI GPT models provide the reasoning layer, while QommonsAI adds public-sector controls so administrators can inspect feature-usage history and restrict model availability according to policy. Polimill also uses Codex across its own development lifecycle—from requirements and code-consistency checks to implementation and testing—which accelerated validation cycles with municipal users and helped the company evolve the system toward a broader public OS and future super-agent marketplace called Qommons ONE.

Data flow

Assembly minutes and administrative records from municipalities are standardized, enriched with metadata, and made searchable through QommonsAI. Public-sector workers query that shared knowledge base through GPT-powered interfaces, while Polimill’s internal team uses Codex to rapidly build and refine the platform from municipal feedback.

Solution architecture

4 components · 3 layers
  1. Compute
    • OpenAI API Provides the model interface used to power QommonsAI and related public-sector features.
    • GPT models Supply the broad reasoning and daily-work assistance used by public employees inside QommonsAI.
  2. Serving
    • QommonsAI Serves as the shared municipal AI platform for assembly responses, public services, social welfare, and legal search.
  3. Orchestration
    • Codex Accelerates Polimill’s own development workflow from requirements through implementation and testing.

Architecture clues

  • Administrative information is standardized and enriched with metadata before retrieval
  • Administrators can review feature-usage history and restrict which models are available by policy
  • Codex is used across requirements definition, implementation, and testing
  • Polimill plans Qommons ONE as a super-agent store for specialized AI systems and apps

Evidence from the source

"About 1,050 municipalities and about 550,000 public employees across Japan now use it."
"Polimill collected and standardized assembly minutes from across Japan, then used AI to add metadata and build a high-precision search foundation"
"QommonsAI includes operational controls that let administrators review feature usage history and limit which models are available according to organizational policy."
"The company adopted Codex across the workflow... implementation, and testing."
Transparency Evidence & methodology 90/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. OpenAI

    Polimill customer story

    First-party
    https://openai.com/index/polimill/
    Source type
    Vendor-published customer story
    Published
    Aug 31, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Aug 31, 2026 · OpenAI · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.