Reduce context switching
Pull tickets, alerts, topology, runbooks, knowledge, owners, and collaboration into one surface.
Product
Bring tickets, alerts, dependencies, runbooks, AI recommendations, approvals, collaboration, and customer impact into a single operating surface.
Prioritize work by SLA risk, service health, customer impact, and AI confidence.
How it works
Pull tickets, alerts, topology, runbooks, knowledge, owners, and collaboration into one surface.
Tune views for agents, responders, service owners, managers, executives, and approvers.
Show AI recommendations with confidence, policy fit, evidence, rollback readiness, and impact.
Connect every action to service health, SLA exposure, automation impact, and audit evidence.
Product capabilities
Prioritize work by business impact, SLA risk, service health, and AI confidence.
See timeline, topology, evidence, probable cause, and recommended actions in one view.
Sync actions and decisions across Slack, Teams, email, and ITSM systems.
Review AI actions with context, blast radius, rollback plans, and policy checks.
Track MTTR, ticket deflection, recurrence, cost impact, and SLA exposure.
Give executives, responders, managers, and service owners the context they need.
Use cases
Prioritize incidents, requests, changes, and alerts by impact, SLA risk, and readiness.
Show timeline, graph impact, probable cause, recommended action, and evidence in one place.
Route AI actions and changes through contextual approval with rollback and policy details.
Keep Slack, Teams, email, ITSM, and war-room updates connected to the official record.
Measure MTTR, deflection, recurrence, SLA exposure, automation quality, and owner accountability.
Give support, SRE, NOC, managers, service owners, and executives the view they need.
How NuralAI automates work
Live product workspace
Service Operations Workspace connects signals, graph context, policy, approvals, automation, and evidence in one NuralAI operating model.
Business outcomes
reduction model in tool switching
faster governed decisions
work prioritized by impact
actions linked to audit trail
Third-party software integrations
NuralAI brings existing ITSM, observability, cloud, identity, CI/CD, security, and collaboration systems into the same product operating model.
Every connector feeds the same signal, graph, workflow, AI decisioning, and audit model.
Tickets, requests, changes, approvals, and collaboration context.
Signals, health, topology, escalations, logs, and event context.
Assets, projects, resources, posture, policy, and cost signals.
Access, deployment events, ownership, controls, and release context.
Resources for you
See tickets, alerts, graph context, approvals, and AI recommendations together.
OpenPlan roles, queues, collaboration, approval, and evidence models.
OpenEstimate MTTR, queue, approval, and productivity impact.
OpenReview approval, policy, evidence, and audit capabilities.
OpenFrequently asked questions
Support agents, SREs, NOC teams, service owners, approvers, managers, and executives can use role-aware views of the same operational context.
Yes. NuralAI connects ITSM, observability, cloud, identity, collaboration, CI/CD, and security systems into one operating view.
AI recommendations appear with confidence, graph context, policy fit, evidence, and approval state before action.
Executives can use summarized views through the Executive Command Center while operational teams continue working in detailed views.
Powered by the NuralAI AI Platform
Bring tickets, alerts, dependencies, runbooks, AI recommendations, approvals, collaboration, and customer impact into a single operating surface.
AI Product Surface
NuralAI product pages now show the actual work pattern buyers inspect: graph-grounded recommendations, policy-aware agents, human-in-the-loop approval, AI-generated remediation plans, model traceability, and executive value updates.
Product signal is correlated against services, owners, cloud resources, and SLA risk.
SignalAI-generated remediation plan cites graph evidence, runbook, confidence, and rollback.
AIPolicy engine decides whether autonomous action is allowed or human approval is required.
GateModel trace, approver, action result, and value impact are stored for audit.
Evidence