Unified signal intake
Ingest tickets, alerts, traces, logs, cloud events, identity activity, costs, changes, and collaboration updates into one operating layer.
Architecture
Sense. Graph. Decide. Act. Govern.
NuralAI connects signals, service relationships, policies, workflows, and AI decisions into one auditable operating model.
Architecture Map
Governed AI active
Incident timeline
Signal ingested from observability stack
Graph impact: payments API, 4 services
AI plan requires approval: restart pool
Runbook executed with rollback ready
Agent confidence
96policy aligned
Graph CMDB
Actions
Approve runbook
Open audit trail
Features
How NuralAI turns fragmented tools into one autonomous operating model.
The architecture is built around a shared signal layer, graph CMDB, AI decisioning, workflow execution, and governance fabric.Graph-native context
Resolve every signal against services, owners, dependencies, business impact, policy controls, and change history.
Policy-aware AI
Ground agents in runbooks, knowledge, graph context, confidence thresholds, and approval requirements before action is recommended.
Workflow execution
Coordinate remediation, ticket updates, owner notifications, change gates, rollback plans, and evidence capture across connected tools.
Governance fabric
Record model calls, agent reasoning, approval history, execution results, exceptions, and audit evidence for operational review.
Composable integrations
Connect ITSM, observability, cloud, identity, CI/CD, collaboration, and security systems without forcing rip-and-replace migration.
NuralAI AI Platform
AI that understands your operations and takes governed action.
Sense
Ingest alerts, logs, tickets, traces, cloud events, and service health.
Graph
Map every signal to services, owners, dependencies, changes, and business impact.
Decide
Ground AI in runbooks, policies, prior incidents, and graph context.
Act
Execute approved workflows across ITSM, cloud, observability, and collaboration tools.
Govern
Audit every AI decision, model call, human approval, and remediation step.
Integration fabric
Connect the tools enterprises already run.
NuralAI is designed to connect ITSM, observability, cloud, identity, CI/CD, collaboration, and security tools without forcing a rip-and-replace migration. Each connector feeds the same graph, AI, workflow, and audit model.
Live connector fabric
12 domains
Graph-aware
Policy-routed
NuralAI AI Platform
Every connector feeds the same signal, graph, workflow, AI decisioning, and audit model.
SenseGraphDecideActGovern
Service workflow
Tickets, requests, changes, approvals, and collaboration context.
IT
ITSM
Incidents and requests
JR
Jira
Engineering work
SL
Slack
War-room updates
TM
Teams
Approvals and owners
Observability
Signals, health, topology, escalations, logs, and event context.
PD
PagerDuty
Escalation state
DD
Datadog
Metrics and traces
SP
Splunk
Logs and searches
Cloud and infrastructure
Assets, projects, resources, posture, policy, and cost signals.
AW
AWS
Accounts and assets
AZ
Azure
Subscriptions
GC
GCP
Projects and services
Identity and delivery
Access, deployment events, ownership, controls, and release context.
OK
Okta
Identity context
GH
GitHub
Deployments and code
CI
CI/CD
Release signals
Architecture in practice
Every integration becomes operational context, not just another data feed.
When NuralAI receives a signal, the platform identifies the service, owner, policy boundary, recent changes, customer impact, runbook path, and approval requirements before agents recommend or execute a workflow.
Watch Architecture DemoDetect
Normalize signals from observability, ITSM, cloud, and collaboration tools into one incident context.
Understand
Use the graph to map dependencies, ownership, risk, service criticality, and change history.
Resolve
Execute approved workflows and capture evidence across tickets, runbooks, notifications, and audit trails.
Resources
Architecture materials for enterprise review.
Use these resources to plan integration scope, operating model, governance controls, and phased implementation.NuralAI platform architecture model
Review how NuralAI combines signals, graph intelligence, AI agents, workflows, governance, and connected systems.
OpenArchitecture walkthrough
See a signal move from ingestion to graph context, AI decisioning, approved remediation, and audit evidence.
OpenIntegration readiness checklist
Prepare ITSM, observability, cloud, identity, CI/CD, collaboration, and security connectors for rollout.
OpenGoverned AI implementation path
Plan phased adoption across service management, operations, cloud control, FinOps, and executive reporting.
OpenPlatform AI Control Plane
The platform exposes how NuralAI senses, reasons, governs, acts, and proves.
NuralAI combines data ingestion, graph context, agent reasoning, policy engine, approval gates, execution connectors, audit/model trace, security boundaries, and deployment controls.
NuralAI AI RuntimeModel trace active
Tickets, alerts, telemetry, cloud events, IAM, cost, changes, and knowledge are normalized.
DataAgents use graph-grounded recommendations instead of isolated prompt responses.
AgentPolicy gates, approval thresholds, identity scope, and rollback plans control action.
PolicyEvery prompt, model result, human approval, connector call, and outcome is auditable.
Trace