Teaching AI Correctly About All Japanese Companies.
Compalyze Inc. announced its 'April Dream' to transform fragmented Japanese corporate data into structured, AI-ready information. They are manually curating and structuring data from various government sources to solve AI's inability to answer complex corporate queries.
📋 Article Processing Timeline
- 📰 Published: April 2, 2026 at 01:45
- 🔍 Collected: April 1, 2026 at 17:37
- 🤖 AI Analyzed: April 21, 2026 at 07:15 (469h 37m after Collected)
We support April Dream, an initiative to make April 1st a day to broadcast dreams. This press release is the dream of Compalyze Inc.
Compalyze Inc. (Kusatsu City, Shiga Prefecture; CEO: Takashi Suzuki), which operates the corporate information database "Compalyze", declares the dream we want to achieve on the occasion of "April Dream" on April 1st.
## Try asking AI. It probably "cannot answer".
Try asking ChatGPT, Claude, or Gemini. Ask them this:
"Tell me about manufacturing companies in Shiga Prefecture that have food-related permits and whose latest financial results are in the black."
You probably won't get an accurate answer. Plausible company names might be listed, but the presence or absence of permits is a guess, the financial figures have no sources, and sometimes even non-existent companies are mixed in.
This is not because AI is immature. It is because the "correct data" that AI can refer to does not exist in the first place.
## Corporate data "exists". But it's scattered and unreadable.
Information about Japanese corporations actually exists in massive amounts. The problem is that they are scattered in different places, in different formats, and with different update frequencies.
Registration information is at the Legal Affairs Bureau. Financial statements are in the official gazette. Patents and trademarks are at the Patent Office. Permits and licenses are divided by ministries—the Ministry of Health, Labour and Welfare, the Ministry of Land, Infrastructure, Transport and Tourism, the Ministry of Agriculture, Forestry and Fisheries. Moreover, Legal Affairs Bureau registrations are PDFs, official gazette financial statements are image data, and each ministry's permit ledger is in Excel or CSV; there is no unified format.
In other words, the data is not "missing," but "not in a usable state." This is the root cause of why AI cannot accurately answer questions about Japanese companies.
## Taking on the gritty work that AI cannot do
What Compalyze tackles every day is the process of polishing this "unusable data" into "quality that AI can trust."
The content of this work is surprisingly mundane and gritty.
Reading PDFs of financial statements published in the official gazette with OCR and converting the numbers into structured data. Correctly distinguishing and classifying "assignment of claims" and "creditor protection procedures" from the registration reception book. Tracing the history of address changes and trade name changes to accurately integrate information on the same corporation. Distinguishing between dormant companies and operating companies. Linking permit data scattered across five or more ministries to a single corporate number. And matching "are these financial figures true?" across multiple sources.
There are no shortcuts in this work. It is an area where human curation is indispensable and cannot be entirely entrusted to AI. Currently, Compalyze's database has reached 90 tables and tens of millions of records. Regardless of whether they are listed or unlisted, it is the "correct resume" of a company, consisting only of primary information with clear sources—registrations, financial results, trends in the number of employees, news, and permits.
AI is smart. However, if it has no data to consume, it can answer nothing. Moreover, if it consumes garbage, it will return garbage. Compalyze creates a state where "AI can consume reliable data."
Compalyze Inc. (Kusatsu City, Shiga Prefecture; CEO: Takashi Suzuki), which operates the corporate information database "Compalyze", declares the dream we want to achieve on the occasion of "April Dream" on April 1st.
## Try asking AI. It probably "cannot answer".
Try asking ChatGPT, Claude, or Gemini. Ask them this:
"Tell me about manufacturing companies in Shiga Prefecture that have food-related permits and whose latest financial results are in the black."
You probably won't get an accurate answer. Plausible company names might be listed, but the presence or absence of permits is a guess, the financial figures have no sources, and sometimes even non-existent companies are mixed in.
This is not because AI is immature. It is because the "correct data" that AI can refer to does not exist in the first place.
## Corporate data "exists". But it's scattered and unreadable.
Information about Japanese corporations actually exists in massive amounts. The problem is that they are scattered in different places, in different formats, and with different update frequencies.
Registration information is at the Legal Affairs Bureau. Financial statements are in the official gazette. Patents and trademarks are at the Patent Office. Permits and licenses are divided by ministries—the Ministry of Health, Labour and Welfare, the Ministry of Land, Infrastructure, Transport and Tourism, the Ministry of Agriculture, Forestry and Fisheries. Moreover, Legal Affairs Bureau registrations are PDFs, official gazette financial statements are image data, and each ministry's permit ledger is in Excel or CSV; there is no unified format.
In other words, the data is not "missing," but "not in a usable state." This is the root cause of why AI cannot accurately answer questions about Japanese companies.
## Taking on the gritty work that AI cannot do
What Compalyze tackles every day is the process of polishing this "unusable data" into "quality that AI can trust."
The content of this work is surprisingly mundane and gritty.
Reading PDFs of financial statements published in the official gazette with OCR and converting the numbers into structured data. Correctly distinguishing and classifying "assignment of claims" and "creditor protection procedures" from the registration reception book. Tracing the history of address changes and trade name changes to accurately integrate information on the same corporation. Distinguishing between dormant companies and operating companies. Linking permit data scattered across five or more ministries to a single corporate number. And matching "are these financial figures true?" across multiple sources.
There are no shortcuts in this work. It is an area where human curation is indispensable and cannot be entirely entrusted to AI. Currently, Compalyze's database has reached 90 tables and tens of millions of records. Regardless of whether they are listed or unlisted, it is the "correct resume" of a company, consisting only of primary information with clear sources—registrations, financial results, trends in the number of employees, news, and permits.
AI is smart. However, if it has no data to consume, it can answer nothing. Moreover, if it consumes garbage, it will return garbage. Compalyze creates a state where "AI can consume reliable data."