Read-oriented integration
Connectors read from historians, control gateways, CMMS, ERP and document stores through approved interfaces.
Platform
One reasoning layer above your existing industrial systems.
Zimam does not replace your historian, CMMS or ERP. It reads from them, builds engineering context, reasons about consequence, and produces decisions your teams can approve and execute.
Intelligence architecture
Seven layers, from raw signal to approved action.
Each layer is independently governed. Data flows upward; authority flows downward.
- 01
Data and system connectors
Historians, SCADA gateways, IoT platforms, CMMS, ERP, document repositories and field reporting — read through governed, approved integrations.
- Historian / SCADA
- CMMS
- ERP & finance
- Documents
- Workforce & HSE
- 02
Industrial knowledge layer
Manuals, drawings, procedures, standards and past investigations parsed into retrievable engineering knowledge with source traceability.
- Manuals & P&IDs
- Procedures
- Standards
- Investigation history
- 03
Context and asset relationships
Assets, processes, dependencies, criticality, operating envelopes and organisational responsibility modelled as one connected context.
- Asset hierarchy
- Process dependencies
- Criticality
- Constraints
- 04
Agentic reasoning and orchestration
Specialised reasoning agents investigate signals, retrieve engineering evidence, test hypotheses and assemble an explainable diagnosis.
- Diagnosis
- Evidence retrieval
- Hypothesis ranking
- Consequence analysis
- 05
Simulation and decision engine
Candidate interventions compared across production, cost, safety, workforce and regulatory criteria to produce a next-best action.
- Option comparison
- Value at risk
- Deferral risk
- Next-best action
- 06
Human approval and governance
Role-based review, explicit authorisation, audit evidence and access controls. No operational action occurs without recorded human approval.
- Role-based access
- Approval routing
- Audit trail
- Explainability
- 07
Learning and performance measurement
Outcomes are recorded against recommendations so accuracy, acceptance and realised value improve with every decision cycle.
- Outcome capture
- Accuracy tracking
- Acceptance rate
- Realised value
How Zimam works
The decision path, stage by stage.
- 01
Connect
Integrate industrial and enterprise data without replacing existing systems.
- 02
Understand
Build context around assets, processes, constraints and operational objectives.
- 03
Diagnose
Identify anomalies, probable root causes, dependencies and consequences.
- 04
Decide
Compare actions using production, cost, safety, workforce and regulatory criteria.
- 05
Act and Learn
Generate an approved execution plan, record outcomes and improve future recommendations.
A human approval checkpoint sits before any operational execution. Zimam recommends; authorised people decide.
Integration posture
Additive by design.
Zimam is deployed as an intelligence layer alongside operational technology, not inside the control loop.
No control authority by default
Zimam issues no set-point or control action. Any future write path requires explicit, contracted authorization.
Existing systems retained
Your historian, CMMS and ERP remain the systems of record. Zimam adds the reasoning between them.
Deployment flexibility
Deployment topology and data residency are configured to the customer's operating environment.
Evidence-linked outputs
Every conclusion carries its supporting signals, documents and assumptions.
Progressive scope
Start on a single asset or decision domain, then extend by unit, site and enterprise.
Security, deployment, and governance configurations are defined according to each customer's operational environment and requirements.
Start with one high-value industrial decision.
Bring us the asset, process, or operational problem. We will help determine whether it is suitable for a focused Zimam pilot.