Data gap
Information is fragmented or difficult to review historically across PLCs, SCADA, historians, meters, spreadsheets, and notes.
Expert-Enabled Managed Intelligence
Continuous plant intelligence, strengthened by human expertise.
PlantIQ continuously organizes plant data, surfaces meaningful changes, and preserves the evidence. Qualified maintenance, process, energy, or electrical experts can then review the findings, add operating context, recommend practical checks, and help your team prioritize action.
Every decision remains with the plant; every outcome becomes reusable learning.
Findings queue · Weekly review
Open
12
This week
5
Verified
3
Pump P-204 power drift
Evidence + recommended checks
Air use overnight
Evidence + recommended checks
Feeder 3 event cluster
Evidence + recommended checks
Illustrative example: sample data, not a customer result.
Why this model
Why this model exists
Attention gap
Plant teams cannot continuously investigate every signal and recurring deviation while running the operation.
Expertise gap
The right maintenance or process specialist may not be available at the right time, especially across multiple plants or specialized equipment.
Dashboards alone do not close these gaps. Pure consulting is episodic and difficult to scale.
Managed Intelligence combines persistent software visibility with scheduled expert interpretation and an accountable action loop.
Operating loop
Continuous monitoring, strengthened by expert judgment
Expert-Enabled Managed Intelligence combines persistent software visibility with scheduled specialist review and an accountable action loop.
- 1.Connect and contextualize
Secure plant data into an asset and process model with limits and baselines.
- 2.Monitor continuously
Keep current state, trends, events, and derived KPIs under watch.
- 3.Surface meaningful change
Package drift, repeated trips, performance loss, and evidence, not noise.
- 4.Expert review
Qualified specialists interpret evidence in plant context.
- 5.Recommend and prioritize
Turn interpretation into practical next steps with confidence and priority.
- 6.Plant decision and execution
The customer remains in control of approval and work execution.
- 7.Verify and learn
Confirm results and improve reusable rules and playbooks.
Operating loop detail
Seven stages from plant data to verified learning
Each stage has a job. Experts interpret evidence; the plant retains authority.
- 1
Connect and contextualize
Secure plant data into an asset and process model with limits and baselines.
- Secure plant data
- Asset/process model
- Operating limits and baselines
- 2
Monitor continuously
Keep current state, trends, events, and derived KPIs under watch.
- Current state
- Trends
- Events
- Derived KPIs
- 3
Surface meaningful change
Package drift, repeated trips, performance loss, and evidence, not noise.
- Rule findings
- Drift
- Repeated trips
- Performance loss
- Evidence packet
- 4
Expert review
Qualified specialists interpret evidence in plant context.
- Validate the signal
- Compare plant context
- Form hypotheses
- Request missing evidence
- Apply domain playbook
- 5
Recommend and prioritize
Turn interpretation into practical next steps with confidence and priority.
- Recommended checks
- Operational or maintenance actions
- Priority and confidence
- Expected benefit/risk
- 6
Plant decision and execution
The customer remains in control of approval and work execution.
- Customer approves
- Owner assigned
- Work carried out through existing plant processes/CMMS
- 7
Verify and learn
Confirm results and improve reusable rules and playbooks.
- Compare before/after
- Confirm result
- Capture notes
- Improve rules/playbook
- Reuse across similar assets and plants
Roles
Four responsibilities. One accountable loop.
Software, experts, partners, and plant teams each own a clear part of the work.
PlantIQ platform
- Connects and stores agreed data
- Maintains plant/asset/process context
- Calculates agreed KPIs and baselines
- Surfaces findings and evidence
- Tracks recommendations and actions
- Provides reports and audit trail
Domain expert
- Reviews findings at the agreed cadence
- Applies maintenance/process/energy/electrical knowledge
- Challenges false positives and weak evidence
- Recommends checks and next actions
- Records reasoning, assumptions, and confidence
- Helps refine reusable playbooks
Local integrator or service partner
- Enables OT connectivity and approved PLC/OPC changes
- Performs field inspection or instrument validation
- Implements approved technical changes
- Provides local support
- Feeds completion evidence back into PlantIQ
Customer plant team
- Owns operating and safety decisions
- Confirms process context
- Approves actions
- Assigns work
- Records outcomes and constraints
- Validates operational and financial impact
Deliverables
Make the service tangible
Managed Intelligence is not a vague retainer. Customers should know what they receive.
- Live and historical plant views
- Prioritized findings queue
- Evidence cards with relevant trends/events
- Weekly, biweekly, or agreed expert review
- Monthly operational-intelligence report
- Review meeting with decision log
- Incident or recurring-problem deep dives
- Recommended inspection/checklist
- Action register with owner, due date, and status
- Before/after verification
- Reusable asset/process playbooks
- Optional multi-site benchmarking where comparable
Recommendation card
Evidence, interpretation, and next checks, without false certainty
A useful recommendation separates what is known from what still needs field validation.
Findings queue · Weekly review
Open
12
This week
5
Verified
3
Pump P-204 power drift
Evidence + recommended checks
Air use overnight
Evidence + recommended checks
Feeder 3 event cluster
Evidence + recommended checks
Illustrative example: sample data, not a customer result.
Recommendation · Pump P-204
Illustrative example
Pump P-204 operating outside expected flow/power relationship
Evidence
Power +14% at comparable flow; discharge pressure unstable; three short trips in 10 days
Expert interpretation
Possible restriction, valve position issue, impeller wear, or instrumentation drift. Evidence is insufficient to identify one root cause remotely.
Recommended checks
- Verify valve state
- Inspect suction restriction
- Validate flow and pressure instruments
- Review impeller condition at next planned stop
Owner
Maintenance manager
Status
Under review
Verification
Compare normalized power and pressure stability after action.
Illustrative example: sample data, not a customer result.
Service tiers
Choose the depth of expert coverage
No public pricing here: tiers describe scope and operating model.
Platform
Best for: Teams ready to own review with strong internal expertise
- Live and historical applications
- Customer-managed review
- Rule-based findings where configured
- Standard support
Guided Intelligence
Best for: A focused plant area or solution family
- Platform plus scheduled expert review
- Monthly findings and recommendations
- Action and outcome tracking
Managed Intelligence
Best for: Critical systems, asset groups, or plants lacking specialist coverage
- Continuous monitoring and agreed review cadence
- Prioritized finding queue
- Regular expert/plant operating review
- Incident deep dives
- Playbook development and performance verification
Fleet / OEM Managed Intelligence
Best for: Multi-site installed base and service organizations
- Multi-site or installed-base monitoring
- Expert review across similar equipment
- Customer portal
- Standardized service playbooks
- Escalation to field service
- White-label/co-branded delivery where agreed
Governance
Boundaries that increase trust
Managed Intelligence is decision support. Operating authority stays with the plant.
- PlantIQ is decision support, not autonomous control.
- Recommendations are based on available data and declared assumptions.
- The customer retains operating, maintenance, safety, and compliance authority.
- Field validation may be required before diagnosis or action.
- Service cadence and response expectations are contract-defined.
- 24/7 emergency monitoring is not implied unless explicitly contracted.
- Experts must be qualified for the relevant equipment/process and operate within documented scope.
- Customer data is not used across customers without permission and appropriate anonymization/aggregation.
- Recommendations, evidence, decisions, and outcomes must be auditable.
Commercial value
Why the model compounds
Scarce expertise becomes reusable. Reviews start from evidence, not exports.
- Extends scarce specialist expertise across more assets and sites.
- Makes consulting recurring and evidence-based rather than episodic.
- Reduces the time spent gathering and cleaning data before every review.
- Converts tacit expert knowledge into reusable playbooks.
- Helps plant teams prioritize planned work.
- Builds a recurring revenue model for PlantIQ and qualified partners.
- Creates a compounding product advantage as asset templates and validated playbooks improve.
Starting packages
Begin with one critical decision
Three focused offers that map cleanly to common plant priorities.
Rotating Equipment Review
Focused managed-intelligence coverage for critical rotating assets with evidence packets and scheduled specialist review.
- Pumps
- Motors
- Fans
- Compressors
Utilities Performance Review
Continuous utility visibility plus expert review of intensity, peaks, and system performance opportunities.
- Refrigeration
- Compressed air
- Boilers and steam
- Water
- Electricity
Critical Process Review
Process-aware monitoring for thermal and sanitation cycles and recurring production-loss conditions.
- Pasteurization
- CIP
- Thermal processes
- Recurring production-loss conditions
FAQ
Common questions about Managed Intelligence
Clear boundaries help plants and partners adopt the model with confidence.
Is Managed Intelligence predictive maintenance or autonomous control?
No. PlantIQ Managed Intelligence is decision support. It continuously organizes plant data, surfaces meaningful change with evidence, and supports specialist review. The customer retains operating, maintenance, safety, and compliance authority. Field validation may be required before diagnosis or action.
Which solution families fit Managed Intelligence best?
Reliability & Asset Intelligence is the strongest initial fit. The same operating model can also support utilities performance, critical process reviews, production-loss investigations, and electrical asset service use cases when data quality and specialist scope are defined.
What does a plant receive each review cycle?
Typical deliverables include a prioritized findings queue, evidence cards, an agreed expert review cadence, monthly operating-intelligence reporting, incident deep dives when needed, an action register with owners and status, before/after verification, and reusable asset or process playbooks.
Do you provide 24/7 emergency monitoring?
Not by default. Service cadence and response expectations are contract-defined. Managed Intelligence should not be assumed to replace plant emergency response, protection engineering, or safety-critical control systems unless explicitly scoped and contracted.
Next step
Design a managed-intelligence pilot around one critical decision.
Choose a rotating-equipment set, utility system, or critical process. We will define data scope, review cadence, deliverables, and governance before expanding.