Our mission
Closing the information gap in investing, through technology.
Information about listed companies is made equally available to everyone through TDnet, EDINET and various news outlets. In reality, however, there is a big difference between institutional investors who subscribe to dedicated terminals and individual investors who make the rounds of free sources on their own, in "selecting information," "reading it" and "speed."
AgeLab provides a service that closes this information gap by combining the information-processing know-how used on the front lines of institutional investing with the latest AI and machine learning technology.
Our story
AgeLab started from one simple question.
"Without a Bloomberg terminal, couldn't we receive just the information we really need,
at the same speed as institutional investors?"
One of our founding members spent their days as a buy-side analyst at a foreign asset management firm, reading large volumes of earnings reports, timely disclosures and overseas news every day. The realization that the accuracy of investment decisions depends on "how quickly you can extract only the important information" became the foundation of the service's design philosophy.
Then a machine learning engineer joined. LLM and AI technology had made it possible to automate and scale "importance rating," "summarization" and "translation," which until then had depended on individual analysts' experience and intuition.
"Build the tool we really wanted, with our own hands." The analyst defines the requirements and the machine learning engineer implements them — and what was born is the investment information service KabuNew, which uses AI to automatically summarize timely disclosures, earnings and company news and notifies you instantly.
Our strengths
Practical experience (Experience)
We reflect directly in our feature design the experience of performing timely disclosure and earnings analysis on the front lines of institutional investing, as analysts at foreign asset management firms.
Technical expertise (Expertise)
Our machine learning engineers' implementation skills in LLMs and natural language processing deliver earnings PDF summaries, translation and automatic stock price impact rating with high accuracy.
Reliable sources (Trust)
We connect directly to primary information such as the TSE's TDnet and the FSA's EDINET. We handle only official information that listed companies themselves have disclosed, not speculation.
Investment decisions are ultimately the investor's own responsibility. That's exactly why we are thoroughly committed to the quality and speed of the "information" that is the entry point to those decisions.
About the team
AgeLab is a small, elite team of members with backgrounds in financial practice and AI / machine learning. Without dividing roles too rigidly, analysts and engineers alike refine the product starting from "the value that reaches investors."
Details about our members' backgrounds and the projects we're working on are available on our corporate site.
Our service
KabuNew (kabunew)
A stock monitoring service that uses AI to automatically summarize TDnet timely disclosures, EDINET statutory disclosures and various company news, rates their impact on the stock price, and notifies you instantly.
Company overview
| Company name | AgeLab Inc. (エイジラボ株式会社) |
| Business | Planning, development and operation of investment information services using AI and machine learning |
| Main service | KabuNew (kabunew.jp) — AI summaries of timely disclosures, earnings and company news / instant notification service |
| Corporate site | https://age-lab.jp/ |
| Disclosure of required items | For inquiries about the items that must be displayed under the Specified Commercial Transactions Act, such as address, phone number and representative, please see the notice under the Specified Commercial Transactions Act page. |
Contact
For questions about the service, press inquiries and business partnership consultations, please contact us through the contact form on our corporate site.
Go to the contact form