Page title: Digital Twin
AI‑driven asset modeling that mirrors entities, relationships, and behavior—updated in real time.

Problem

Siloed systems and point tools obscure real context.

Diagnosing root cause across assets and processes is slow and manual.

Teams rely on static dashboards that lag behind live conditions.

Solution

- Synapse automatically discovers assets, infers relationships, and maintains a living model of your environment. - Navigate from macro overviews to micro details in seconds, with real-time state and historical context. - Act confidently by connecting insights to orchestration and workflows.

Core Capabilities

Automatic asset discovery and classification from live streams

Relationship and dependency graph with context metadata

Real-time state sync and lifecycle management

Multi-level visualization (fleet → site → line → asset → component)

Time travel and event replay for investigations

Access controls, audit trails, and data lineage

How It Works

  1. Step 1
    Ingest data from PLCs, IoT sensors, EMR/BMS/ERP, and APIs via the Data Fabric
  2. Step 2
    AI models infer entities and relationships; build/update the twin graph
  3. Step 3
    Stream processing updates state and KPIs in real time
  4. Step 4
    Visualize and query; push actions via orchestration to downstream systems

Integrations

Industrial: OPC‑UA, Modbus, MQTT, SCADA, historians

Enterprise: ERP (SAP/Oracle), MES, CMMS/EAM, CRM, ITSM

Building/Healthcare: BACnet, EMR/EHR, HL7/FHIR

Cloud: REST/GraphQL, webhooks, files, streams

KPIs & Outcomes

30–60% faster root‑cause analysis

15–25% reduction in downtime via earlier detection

1–2 hours/week saved per user on data hunting

Security & Governance

RBAC/ABAC for model and data access

Data in transit and at rest encryption

Governance: lineage, audit logs, change history

See Synapse in action

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