Teserac provides an AI-native platform called Neuron™ that delivers unified observability and automated, real‑time decision‑making for data center operations. By ingesting telemetry from all infrastructure systems, it correlates events, surfaces actionable insights, and codifies senior engineers’ expertise into automated workflows, reducing human‑error‑driven downtime and accelerating onboarding of new technicians.
Funding
Funding not disclosed
Founders
Product
Problem
Data center operations rely on fragmented monitoring tools, manual ticketing, and tribal knowledge, leading to slow root‑cause analysis and frequent human‑error‑driven downtime. As senior engineers retire, critical expertise is lost, leaving new technicians unable to respond quickly to incidents.
Solution
Teserac’s Neuron™ platform provides a unified, AI‑native observability layer that ingests real‑time telemetry from all infrastructure systems and creates a live digital twin of the facility. The platform applies AI‑driven anomaly detection and event correlation to surface actionable insights automatically, turning alerts into prescribed remediation steps. By embedding senior engineers’ expertise into intelligent workflows, Neuron™ accelerates root‑cause analysis, reduces manual ticketing, and enables consistent, automated responses across shifts and sites. The continuous learning loop improves accuracy as each resolved incident enriches the knowledge base, helping teams prevent future outages and lower downtime costs.
Target Audience
Primary customers are data center operators, infrastructure managers, and IT teams responsible for mission‑critical facilities that require high availability and rapid incident response.
Features
- Real‑time ingestion of telemetry from power, cooling, networking, and rack‑level equipment into a single observability graph
- Live digital twin visualization that maps every node with up‑to‑date status overlays
- AI‑based anomaly detection and cross‑system correlation to identify root causes without manual analysis
- Automated workflow engine that converts alerts into prescriptive actions and ticket generation
- Knowledge capture module that codifies senior engineers’ procedures and applies them across all sites and shifts
- Continuous learning model that refines detection and remediation logic with each resolved incident