SIGQ and Getworks Collaborate on Secure Incident Management with Local LLM on Closed Network

SIGQ and Getworks Join Forces for Secure AI Incident Management

In a significant move towards innovation in incident management, SIGQ, a prominent AI technology startup based in Tsukuba, and Getworks, a leader in container data center operations, have announced their strategic collaboration. This partnership aims to leverage local language models (LLMs) for autonomous incident response while ensuring that sensitive data remains within a closed network—a crucial aspect for organizations in highly regulated sectors such as finance and public infrastructure.

Background of the Collaboration

The frequency of system outages has made downtime a severe risk to enterprise credibility. SIGQ’s flagship product, Incident Lake, employs AI agents that actively aggregate and analyze logs, guiding managers not just to identify what is happening but to focus on essential decision-making. This proactive approach minimizes the time spent on troubleshooting, thus enhancing operational efficiency.

In industries demanding high-security standards, sensitive data cannot be transferred to the cloud, heightening the need for incident management solutions within closed network environments. Additionally, many companies face challenges utilizing public LLMs due to strict security policies that prohibit handling high-risk data online.

By collaborating with Getworks, SIGQ aims to address these challenges head-on. Getworks is recognized for its extensive experience in building and operating over 300 container data centers as well as its cooling GPU infrastructure—essential for the efficient functioning of AI applications like Incident Lake.

Collaboration Details

The partnership focuses on several key initiatives:
1. Joint Development of Local LLM Environment
Building a robust local LLM infrastructure is a primary focus for both companies. By utilizing Getworks' secured GPU environment, they can create a platform compliant with security policies that allow enterprise-level incident response using AI agents without external cloud exposure.
2. Application Infrastructure for Closed Networks
The integration of Incident Lake's core application within closed network architectures will be facilitated using Getworks' infrastructure, ensuring that no data leaves the protected network.
3. Joint Market Expansion in Enterprise Sector
The two companies will collaboratively market the closed network and local LLM-configured Incident Lake to enterprises with high-security requirements, reinforcing their commitment to a secure operational environment.

Leadership Perspectives

Keiaki Kanetsuki, CEO of SIGQ

In his remarks, Kanetsuki expressed his excitement about the collaboration, indicating that many enterprise clients have voiced the need for Incident Lake while also being unable to send data to the cloud. This partnership enables SIGQ to provide a secure solution that combines a closed network with local LLM technology, ultimately allowing more businesses to harness the value of autonomous AI incident management.

Hidenori Nakazawa, CEO of Getworks

Nakazawa shared his enthusiasm for collaborating with SIGQ on this advanced incident management initiative. He acknowledged the rising demand for AI operation on domestic infrastructure, especially in sectors handling confidential data. By focusing on the construction of sovereign AI platforms that respect data sovereignty, this partnership aligns with their vision of automating data center operations through AI enhancement.

About SIGQ

Founded in August 2024, SIGQ focuses on automating and improving system operations through AI technology. Their Incident Lake product goes beyond mere efficiency tools; it autonomously manages data collection during incidents, providing real-time visibility to executives and stakeholders, thus solving organizational incident management challenges.

About Getworks

Established in August 2002, Getworks specializes in constructing and operating container data centers and offers water-cooled GPU infrastructure. Its significant experience, totaling over 300 container facility constructions, positions it as a leader in supporting the growing demands for GPU resources while prioritizing data security and sovereignty in AI deployments.