Asilla, an Image Analysis AI Company, Adopts "Incident Lake," an Agentic AI Specialized in Incident Management

SIGQ (Headquarters: Tsukuba, Ibaraki; Representative Director: Takaaki Kanetsuki), developer of the incident management-specialized Agentic AI "Incident Lake," is pleased to announce that its "Incident Lake" platform and professional services have been adopted by Asilla (Headquarters: Machida, Tokyo; Representative CEO: Takeshi Onoue, hereinafter "Asilla"), a company deploying products utilizing its proprietary image analysis AI. Background and Challenges: Knowledge Silos and Language Barriers During Rapid Growth Asilla leverages deep learning for its unique action recognition AI, offering products like "AI Security Asilla" for the security industry, which can be deployed by simply connecting an edge AI server to existing security cameras. While the business is expanding rapidly, the company identified the following challenges in operating its cloud infrastructure and edge AI servers: - Incident response and operational monitoring knowledge tended to be siloed within individual business and product teams. - Language barriers between Japan and Vietnam created overhead, becoming a bottleneck for development and incident response. - As the company sought to scale further, it aimed to strengthen its operational structure and quality. Benefits of Implementation: AI Knowledge Automation and On-site Support To address these issues, Asilla adopted "Incident Lake" and SIGQ's professional services, reporting the following benefits: - Utilization of Incident Lake as a common platform for teams, facilitating the smooth horizontal deployment of incident-related knowledge. - Instant sharing of analysis results and discussion content in multiple languages by the AI, which reduced translation efforts and friction caused by language barriers, thereby smoothing communication. - Provision of operational expertise through professional services, supporting further business scaling, including overseas operations. Comments from Mr. Masahiro Wakasa, CTO of Asilla "Regarding incident response, we felt a need to evolve our operational organization to automate as much as possible, allowing humans to make prompt decisions. The UX of 'Incident Lake' minimizes manual information entry, which allowed us to incorporate it into our operational flow smoothly while reducing resistance from members towards new tools. Furthermore, regarding SIGQ's professional services, I was genuinely surprised that they joined us on-site before official support even began and offered various improvement proposals—I was impressed they would do that much from the start. Thanks to their dedicated support, I am confident this is the necessary service to strengthen our operational structure. We will continue to absorb the knowledge gained from their professional services and Incident Lake to aim for an even more reliable service." Comments from Takaaki Kanetsuki, Representative Director of SIGQ "I am very pleased that our 'Incident Lake' and professional services can contribute to Asilla's innovative solutions that support the safety of social infrastructure. In cross-border development and operational structures, information fragmentation and language barriers are hurdles many growing companies face. By leveraging the power of AI agents, we will continue to provide an environment that eliminates these frictions and allows managers and engineers to focus on high-value-added work. We will provide strong support from the perspective of incident management for Asilla's future global expansion." About "Incident Lake" "Incident Lake" is an "incident intelligence layer" that uses the evolution of cutting-edge LLMs as its engine to integrate scattered operational data and dramatically accelerate decision-making. An "Accumulation Hub" of Knowledge That Sharpens the LLM It goes beyond mere data processing. It ingests "living data"—such as Slack dialogues, information stored in existing ticket management tools (ServiceNow, Atlassian Jira, etc.), and on-site judgments—and stores them within Incident Lake in a format that LLMs can instantly utilize. As data accumulates, the system builds a mechanism where the LLM gains a deeper understanding of the organization's unique rules and past lessons, causing the accuracy of its responses and support to self-evolve. Collaborating with Existing Tools to Turn Operational "Last-Mile" Data into Assets It demonstrates its true value by being used in conjunction with existing ticket management tools rather than replacing them. - Data Assetization: Incident Lake absorbs and structures not just the "results" recorded in existing tools (like ServiceNow), but also the "reasons for decisions" and "trial and error" processes—the last mile of operational data. - Decision-Making Hub: While linking with existing tools, it provides the "organizational wisdom" cultivated within Incident Lake to managers. It minimizes the effort required for information organization, supporting prompt and valid decision-making. Incident Lake updates the way enterprise operations are managed as an "organizational decision-making engine" that gets smarter the more it is used. ▼ Incident Lake Product Introduction Site: https://incidentlake.com ▼ Inquiries regarding Incident Lake implementation and business partnerships: https://incidentlake.com/contact Asilla Inc. Company Name: Asilla Inc. Representative: Representative CEO Takeshi Onoue Date of Establishment: June 2015 Address: 1-4-2 Nakamachi, Machida, Tokyo Corporate URL: https://jp.asilla.com/ SIGQ Inc. Company Name: SIGQ Inc. Representative: Representative Director Takaaki Kanetsuki Date of Establishment: August 2024 Address: Room 203, Tsukuba Industrial Promotion Center, 2-5-1 Azuma, Tsukuba, Ibaraki, 305-0031 Corporate URL: https://company.sigq.io