DG Daiwa Ventures Invests in AI Agent for Institutional Investors 'Project Pluto'
DG Daiwa Ventures announced a Series A investment in Project Pluto Inc., a New York-based startup providing 'Terminal X', an AI financial agent designed for institutional investors.
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- 📰 Published: April 3, 2026 at 22:00
- 🔍 Collected: April 3, 2026 at 18:04
- 🤖 AI Analyzed: April 21, 2026 at 05:23 (419h 18m after Collected)
DG Daiwa Ventures (Headquarters: Chiyoda-ku, Tokyo; Representative Directors: Junichi Nakajima, Katsuyasu Murata; hereinafter 'DGDV') announces its Series A round investment in Project Pluto Inc. (Representative Director: Hyun, Hong; Headquarters: 430 Park Ave, New York; hereinafter 'Project Pluto'), the provider of the AI Financial Agent 'Terminal X'.
**An 'Investment-Specialized AI Agent' that Understands Internal Corporate Data**
Terminal X provides an AI agent capable of indexing public and private data at scale—including the internal data of institutional investors—and executing precise searches and reasoning down to the cell and numerical level. The defining feature of this agent is that it is not merely a search tool; it can execute research and analysis aligning with the actual thought processes of analysts and portfolio managers. It integrates the entire investment workflow into a series of AI workflows, including drafting investment memos, comparable company analysis, transaction precedent analysis, portfolio monitoring, and investment committee preparation.
**Focusing on 'Unstructured Data' Among Institutional Investors**
Institutional investors such as asset management firms, private equity funds, and investment banks possess vast amounts of data, including real-time market data, broker research, internal documents, models, emails, and message histories. However, much of this data exists in unstructured and fragmented forms, making it structurally difficult for AI to utilize immediately. Project Pluto addresses the core of this challenge—the fact that 'investment data exists but is not optimized for LLMs'—by redesigning and rebuilding the data infrastructure from the ground up so that AI can be leveraged in actual investment operations.
**Rapidly Validated Enterprise Traction**
Since its service launch in early 2025, Project Pluto has shown rapid expansion, with enterprise customer usage growing approximately 40-fold in just eight months. To date, over one million enterprise queries have been processed cumulatively, and major clients are executing a significant portion of their core investment operational hours on Terminal X.
Furthermore, the conversion rate from paid PoCs to official contracts is high, recording rapid growth on an ARR basis. These achievements demonstrate product-led scalability, expanding primarily through word-of-mouth referrals among customers without relying on external marketing.
**Competitiveness Based on Finance-Specialized Data Infrastructure**
Built on a data infrastructure specialized for the financial industry, Project Pluto features an architecture that can simultaneously process both public data and internal private corporate data. It can comprehensively analyze large-scale unstructured documents, traditional Excel and time-series data, and real-time market data. Utilizing a multi-model and multi-agent architecture, it provides AI agents optimized for each specific investment task.
Through this, it has established a solid position as a Vertical AI specifically tailored for the financial sector, distinguishing itself from general-purpose AI tools and simple data provision services.
**Investment Background**
DGDV recognized that Project Pluto is deeply integrated into the actual operational workflows of institutional investors.
**An 'Investment-Specialized AI Agent' that Understands Internal Corporate Data**
Terminal X provides an AI agent capable of indexing public and private data at scale—including the internal data of institutional investors—and executing precise searches and reasoning down to the cell and numerical level. The defining feature of this agent is that it is not merely a search tool; it can execute research and analysis aligning with the actual thought processes of analysts and portfolio managers. It integrates the entire investment workflow into a series of AI workflows, including drafting investment memos, comparable company analysis, transaction precedent analysis, portfolio monitoring, and investment committee preparation.
**Focusing on 'Unstructured Data' Among Institutional Investors**
Institutional investors such as asset management firms, private equity funds, and investment banks possess vast amounts of data, including real-time market data, broker research, internal documents, models, emails, and message histories. However, much of this data exists in unstructured and fragmented forms, making it structurally difficult for AI to utilize immediately. Project Pluto addresses the core of this challenge—the fact that 'investment data exists but is not optimized for LLMs'—by redesigning and rebuilding the data infrastructure from the ground up so that AI can be leveraged in actual investment operations.
**Rapidly Validated Enterprise Traction**
Since its service launch in early 2025, Project Pluto has shown rapid expansion, with enterprise customer usage growing approximately 40-fold in just eight months. To date, over one million enterprise queries have been processed cumulatively, and major clients are executing a significant portion of their core investment operational hours on Terminal X.
Furthermore, the conversion rate from paid PoCs to official contracts is high, recording rapid growth on an ARR basis. These achievements demonstrate product-led scalability, expanding primarily through word-of-mouth referrals among customers without relying on external marketing.
**Competitiveness Based on Finance-Specialized Data Infrastructure**
Built on a data infrastructure specialized for the financial industry, Project Pluto features an architecture that can simultaneously process both public data and internal private corporate data. It can comprehensively analyze large-scale unstructured documents, traditional Excel and time-series data, and real-time market data. Utilizing a multi-model and multi-agent architecture, it provides AI agents optimized for each specific investment task.
Through this, it has established a solid position as a Vertical AI specifically tailored for the financial sector, distinguishing itself from general-purpose AI tools and simple data provision services.
**Investment Background**
DGDV recognized that Project Pluto is deeply integrated into the actual operational workflows of institutional investors.