SERVICES
Services
HOW WE WORK
Build the data platform first. Build incident response on top of it.
Most of the difficulty in incident response comes down to a data problem. The logs, metrics, tickets, and chat needed for a decision exist, but they are scattered across systems with no shared data model, no access control, and no retention policy. Facing an attack or an outage in that state, response depends on individuals and accountability after the fact is out of reach. SIGQ was built to change this structure. We build a secure, global-scale data platform first, then combine detection, command, and audit on top of it. That is how we develop Incident Lake.
Everything below runs on the same architecture, data model and security controls we operate in production every day. If it cannot withstand our own on-call operations, we do not ship it.
WHAT WE BUILD AND RUN
One product. One foundation.
Incident Lake
Incident Lake is the agentic AI for incident management that SIGQ builds, operates and uses on its own services. It unifies monitoring, ticketing and chat into one data layer, turns tribal memory into structured institutional knowledge, and generates the audit trail as a by-product of the response rather than reconstructing it afterwards. SLOs, alerting, escalation and postmortems are built into the product, so every incident becomes a measurable improvement.
• Institutional knowledge, captured as data
• Standardized response workflow
• Automated first response
• Executive-level visibility
• Latent-risk identification and analysis
• Integration with existing systems
• Internal controls and evidence management
• Rapid-response readiness
Product details at incidentlake.com
Service 01
Data Platform Engineering
We design and build the data foundation that incident response, observability and compliance all depend on: streaming and batch ingestion, a shared operational data model, role-based access, retention and cost controls, and the lineage auditors ask about. Built for the scale and security posture of regulated enterprises. We design the data governance that regulated enterprises and public institutions require, meaning access control, retention, lineage, and audit trails, as a precondition of the platform rather than an afterthought.
• Retrieval-augmented generation (RAG) pipelines
• High-performance search and vector retrieval
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Questions about our services, press, or partnerships? We reply in English or Japanese.
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