SIGQ Secures JPY 123m in Pre-Series A Funding Lead by Mizuho and SMBC
SIGQ, a developer of autonomous AI solutions for IT operations, has raised a total of 123 million yen (approx. USD $820,000) in the first close of its Pre-Series A funding round. The financing will accelerate the Go-to-Market (GTM) strategy for its flagship product, "Incident Lake," specifically targeting the enterprise sector.
The round represents a hybrid financing structure comprising 93 million yen in equity via J-KISS stock acquisition rights and 30 million yen in debt financing.
The equity portion was backed by major banking venture capital firms Mizuho Capital and SMBC Venture Capital. They were joined by a syndicate of nine angel investors, including current and former executives from leading Japanese tech growth companies such as PLAID, Money Forward, and PKSHA Technology.
Notably, the debt financing component was secured through the Japan Finance Corporation and Joyo Bank. SIGQ obtained these funds under favorable terms rare for early-stage startups—long-term repayment schedules with no collateral or personal guarantees required from the representative—signaling strong institutional confidence in the company’s business model and creditworthiness.
Turning "Tacit Knowledge" into Assets
As SaaS and cloud infrastructure become critical social utilities, the complexity of managing system failures (incidents) has skyrocketed, placing immense strain on engineering teams.
SIGQ’s "Incident Lake" operates as an "Incident Intelligence Layer." It integrates top-tier Large Language Models (LLMs)—including Google’s Gemini, OpenAI’s ChatGPT, and Anthropic’s Claude—into a model-agnostic architecture. The platform automates the aggregation of scattered operational logs and attempts to digitize the "tacit knowledge" and decision-making processes of skilled engineers. By structuring this data, the AI evolves to provide decision support that is specific to the organization's unique context, aiming to reduce the burden on human managers.
Strategic Allocation of Funds
SIGQ plans to deploy the capital to build out its operational structure with a focus on three key areas:
- Enterprise Expansion: The company will establish dedicated Sales and Customer Success (CS) teams to support implementation in industries requiring high reliability and accountability, such as finance, manufacturing, telecommunications, and large-scale SaaS providers.
- Market Education (AIOps): SIGQ intends to increase marketing investment to drive awareness of "AIOps" (Artificial Intelligence for IT Operations), positioning it as the next-generation standard for incident response.
- Partnership Ecosystems: Through collaborations with System Integrators (SIers) and cloud vendors, SIGQ aims to capture the "last mile" of operations—the nuanced decision-making data often missed by existing platforms—and circulate these assets within a new operational ecosystem.
"Incident Lake is designed to be an organizational decision-making engine that gets smarter the more it is used," said Takaaki Kanazuki, CEO of SIGQ. "We are moving beyond general-purpose AI to provide a highly sophisticated support infrastructure that reflects a company's past lessons and specific protocols."
Norbert Gehrke
