The company raised a total of 123 million yen in the first close of its Pre-Series A funding round

SIGQ Co., Ltd. (Headquarters: Tsukuba City, Ibaraki Prefecture; Representative Director: Takaaki Kanetsuki), the developer of "Incident Lake," an agentic AI platform specializing in incident management, has raised a total of 123 million yen in a pre-Series A funding round through a combination of equity financing via the issuance of J-KISS-type stock options and debt financing from financial institutions.

Overview of the Fundraising and Underwriters

In this pre-Series A round, we have secured investment from Mizuho Capital and SMBC Venture Capital, as well as nine individual investors—experts who have driven the growth of some of Japan’s leading SaaS and AI startups.

In addition, regarding debt financing, we secured loans from the Japan Finance Corporation and Joyo Bank under favorable terms for a startup in its early stages, including unsecured and unguaranteed loans (backed by an association guarantee) with long-term scheduled repayment terms. We view this as a sign of strong confidence in our business model and management structure.

Total procurement amount

123 million yen

Breakdown of Procurement

• Equity (93 million yen): Issuance of J-KISS-type stock options

• Debt (30 million yen): Long-term loan with no collateral or guarantees from the representative (backed by an association guarantee)

Investors (titles omitted, listed in no particular order)

[Venture Capital]

• Mizuho Capital Co., Ltd.

• SMBC Venture Capital Co., Ltd.

[Individual Investors]

• Kenta Kurahashi (CEO, Prayed Inc.)

• Naoki Shibayama (Director, Plaid Inc.)

• Yuichiro Kuwano (Executive Officer and CGO, Plaid Inc.)

• Naoki Kuroda (Former Executive Officer, Money Forward, Inc.)

• Yusuke Shimomura (Former Executive Officer, PKSHA Technology Co., Ltd.)

• Ryosuke Igari (Former Director, TENTIAL Co., Ltd.)

• Hiroki Okada (Co-Representative, AX Tax Corporation / Certified Public Accountant)

• Yuki Irie (Co-Representative, AX Tax Corporation / Certified Public Accountant)

• Shinobu Miyahara (External Advisor, SIGQ Co., Ltd.)

Background and Purpose of the Fundraising

As SaaS and cloud services become part of our social infrastructure, the speed of incident response has become a critical factor in ensuring business continuity and reliability. However, due to fragmented information and increasingly complex procedures, engineers and managers on the front lines are facing workloads that are nearing their limits.

A Unique Architecture That Transforms LLM Evolution into "Product Value Enhancement"
"Incident Lake" is an incident intelligence layer that incorporates the evolution of cutting-edge LLMs—such as Google’s Gemini, OpenAI’s ChatGPT, and Anthropic’s Claude—into the core of the product. It accumulates an organization’s "tacit knowledge" and "decision-making processes" as structured data, dramatically accelerating decision-making. Through the synergy of advancing LLM intelligence and deepening accumulated proprietary data, the more it is used, the more an organization’s unique decision-making accuracy is refined, continuously evolving into a one-of-a-kind decision-making support platform.

• Instantly translating LLM advancements into product value: We’ve adopted an architecture that isn’t tied to any specific model. The system is designed so that as the inference capabilities of the underlying LLM improve, analysis accuracy and decision-making speed are automatically enhanced.

• Converting an organization’s “tacit knowledge” into structured data: We collect daily response logs and decision-making criteria (tacit knowledge) that were previously known only to experienced field staff, and structure them into a format that large language models (LLMs) can understand and utilize. This data is then accumulated as a valuable, organization-specific asset.

• "Unique Decision-Making" That Gains Momentum the More You Use It: As data accumulates, LLMs learn more deeply what constitutes the "right answer" for that specific organization. Rather than being merely a general-purpose AI, it continues to evolve into a one-of-a-kind, advanced decision-support platform that reflects your company’s past lessons and decision-making processes.

Purpose of the fundraising: Full-scale launch of the Go-to-Market (GTM) strategy

We will allocate the funds raised in this round primarily to the following three areas to accelerate our organizational growth with a view to achieving scalable expansion in the enterprise sector.

• Launching an Enterprise Division: We are establishing a new Sales and Customer Success (CS) team to support implementations for companies in sectors such as finance, manufacturing, telecommunications and infrastructure, and large-scale SaaS—industries that demand a high level of reliability and accountability.

• Expanding marketing investments: Through trade shows and digital marketing, we will raise market awareness and understanding of next-generation operations (AIOps) with a focus on enhancing decision-making in incident response.

• Monetizing the "Last Mile of Operations" Through Partnerships: Through collaboration with system integrators (SIers) and cloud vendors, we are driving the establishment of "Incident Lake" as a foundational platform within increasingly complex enterprise operational environments.We capture the “last mile of operations”—including on-site decision-making and tacit knowledge that existing platforms could not fully capture—as structured data. By combining this with advancements in large language models (LLMs), we build a new operational ecosystem that circulates and accumulates an organization’s unique decision-making assets.

  *Related Press Release: SIGQ, a provider of Agentic AI, has launched a strategic partnership with Fujitsu’s venture studio, “Fujitsu Launchpad”

About Incident Lake

"Incident Lake" is an "incident intelligence layer" that leverages the latest advancements in large language models (LLMs) to consolidate scattered operational data and dramatically accelerate decision-making.

A "Hub of Knowledge" Where Accumulation Sharpens LLMs

It goes beyond simply processing data from start to finish.It incorporates “live data”—such as conversations on Slack, information stored in existing ticket management tools (ServiceNow, Atlassian Jira, etc.), and on-site decisions—and stores it within the Incident Lake in a format that the LLM can immediately utilize. As more data accumulates, the LLM gains a deeper understanding of “that organization’s specific rules and past lessons,” building a system where the accuracy of its responses and support continues to self-improve.

Working in tandem with existing tools to turn the "last mile" of operations into an asset

Rather than replacing existing ticket management tools, it truly shines when used in conjunction with them.

• Monetizing Data: Incident Lake captures and structures not only the "results" recorded in existing tools (such as ServiceNow), but also the "reasons behind decisions" and "trial and error"—the "last mile" of data—that occur during the process.

• Decision-Making Hub: By integrating with existing tools, it delivers the "organizational wisdom" cultivated within Incident Lake to managers. This minimizes the effort required to organize information and supports rapid, well-informed decision-making.

Incident Lake is an "organization-specific decision-making engine" that gets smarter the more you use it, revolutionizing the way enterprises operate.

▼ Incident Lake Product Overview
https://incidentlake.com

▼ Contact Information for Inquiries Regarding the Implementation of Incident Lake and Business Partnerships
https://incidentlake.com/contact

Comments from investors

Mr. Daisuke Hosoda, Senior Investment Manager, Investment Division 1, Mizuho Capital Co., Ltd.

Mizuho Capital has recently participated in SIGQ’s funding round. As the digital transformation of society accelerates, the number of incidents requiring corporate response is on the rise. While incident managers are increasingly overwhelmed, there is a growing demand for faster, more efficient, and more sophisticated incident response.

Drawing on his extensive hands-on experience, Mr. Kanetsuki has a deep understanding of the challenges faced by those directly involved. I am confident that SIGQ’s products, built on this insight, can provide the essential functionality needed by companies with a diverse range of stakeholders, including financial institutions.

We decided to invest because we believe that only SIGQ and its CEO, Mr. Kanetsuki, can truly elevate companies’ incident response capabilities.
We look forward to continuing to support their growth in whatever small way we can.

Mr. Hayato Magome, Deputy General Manager, Investment Sales Division 4, SMBC Venture Capital Co., Ltd.

SIGQ provides AI-native products that streamline operational workflows for managers overwhelmed by incident response and support advanced decision-making.
We are carefully and swiftly developing solutions that deliver value precisely because AI continues to evolve.

This has been made possible precisely because our CEO, Mr. Kanetsuki, possesses unparalleled knowledge and experience in this field, and we are confident that he will continue to work closely with our enterprise clients—including financial institutions—to gain a deep understanding of their challenges and find solutions to them.

To that end, we intend to leverage the SMBC Group’s resources to support this endeavor as much as possible.

Individual investor (Naoki Kuroda, former Executive Officer of Money Forward, Inc.)

I first met Mr. Kanetsuki, the CEO of SIGQ, when he was still a student writing rough code. From then until now, I have cheered him on as he has grown and made great strides thanks to his innate “overwhelming drive.”

Due to the potential for significant damage to business operations and the high level of difficulty—which requires sophisticated judgment tailored to each situation—incident response has traditionally been entrusted to seasoned engineers with deep knowledge of internal systems.
By aggregating incident-related information and incorporating advancements in large language models (LLMs), “Incident Lake” aims to serve as a substitute for seasoned engineers or as their optimal support.

The evolution of AI is currently having an unprecedented impact on the SaaS industry. What is needed is not merely the adoption of AI, but AI-native product design and team building. I wholeheartedly support SIGQ’s ambitious endeavor to become AI-native.

Individual investor (Mr. Yusuke Shimomura, former Executive Officer of PKSHA Technology Co., Ltd.)

Incident response is an essential part of an organization’s operations. Being on call at night and on holidays can be exhausting, and the greater the burden of trust and accountability, the higher the cost of communication—both internally and externally. On the other hand, if you can capture the tacit knowledge gained from these responses as “knowledge assets” and craft tailored explanations for each customer, this can become a powerful tool for building customer trust.

Mr. Kanetsuki is an outstanding expert in incident response, and I am confident that he will help solve this obvious organizational pain point and social issue. I look forward to a world where “Incident Lake” becomes widely adopted and the challenges of incident response are minimized!

Individual investor (Mr. Shinobu Miyahara, External Advisor to SIGQ Co., Ltd.)

While SaaS and cloud services are becoming part of our social infrastructure, incident response related to operations and systems still relies heavily on individual experience and subjective judgment, making it difficult to accumulate this knowledge as reusable insights for management and the organization.

To address this challenge, Incident Lake employs an approach that uses AI agents optimized for each customer to aggregate and structure information, thereby preserving on-site judgments and response processes as "decision assets."

Through numerous discussions with Mr. Kanetsuki as an external advisor and by supporting the company throughout this funding round, I became convinced that it is not the use of LLMs itself that is the source of value, but rather the company’s deep domain expertise and its ability to translate that expertise into viable businesses and products that truly define its competitive edge.

Given that the company is currently at a stage where it is poised for full-scale enterprise deployment, we believe this is a challenge worth committing to as investors, in addition to the support we have provided thus far.

Comment from Takaaki Kanetsuki, Representative Director of SIGQ Co., Ltd.

In today’s world, where systems are becoming increasingly critical, operations managers bear the heaviest burden and face the most critical decisions when incidents occur. However, in reality, they are often overwhelmed by tasks such as aggregating information and assessing the situation, leaving them little time to focus on their core role: strategic decision-making.

Incident Lake provides an environment where busy managers can leverage AI agents as their right-hand assistants to minimize the time and effort required for information gathering and analysis, enabling them to make the fastest and most accurate decisions. We firmly believe that allowing managers to focus on their core responsibilities and leveraging the time and productivity of high-value talent is the key to maximizing corporate productivity and, ultimately, enhancing corporate value.
Furthermore, by enabling rapid incident response and establishing a proactive prevention system based on accumulated data, we will solidify corporate reliability. Through this funding round, we will vigorously advance our go-to-market strategy and support the operational foundations of numerous companies.