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Physical & IoT AI

Transform Sensor Data Into Operational Decisions

Operational intelligence platforms combine IoT sensor data, computer vision, and AI analytics to give operations managers real-time visibility into facility and process performance — enabling faster decisions, proactive interventions, and continuous improvement based on objective data.

Overview

What RLM Delivers on Operational Intelligence

Operations managers have always relied on lagging indicators — end-of-shift reports, daily production summaries, weekly quality reviews. AI-powered operational intelligence transforms this with real-time visibility and predictive insight that enables intervention before performance deviates significantly.

How We Work

How We Approach Operational Intelligence

Our AI and automation advisory runs from discovery and market evaluation through vendor selection and post-deployment optimization — scoped to the Operational Intelligence decision in front of you.

1

Operational KPI & Data Assessment

We work with your operations leadership to define the KPIs most critical to operational performance and assess the data sources — sensors, PLCs, MES, ERP, cameras — available to drive them, identifying gaps in real-time visibility.

KPI DefinitionData Source AssessmentGap Analysis
2

Operational Intelligence Platform Evaluation

We evaluate platforms — PTC ThingWorx, GE Digital, Cognite, Seeq, and others — against your equipment connectivity, data volume, analytics requirements, and integration with existing operational systems.

Platform EvaluationConnectivity AssessmentAnalytics Requirements
3

Dashboard & Alerting Design

Operational intelligence value is delivered through well-designed dashboards and targeted alerts. We design the visualization architecture and alerting logic that surfaces actionable information without overwhelming operators.

Dashboard DesignAlert LogicUser Experience
4

Predictive Analytics & Continuous Improvement

Beyond real-time visibility, operational intelligence platforms should support predictive analytics — forecasting production output, predicting quality issues, and identifying process optimization opportunities.

Predictive Model DesignContinuous Improvement FrameworkAnalytics Roadmap
What to Evaluate

Operational Intelligence Selection Criteria

The questions below are the ones that decide whether a Operational Intelligence investment pays back — and the ones vendors are least eager to answer.

01

Data Connectivity Breadth

Operational intelligence requires connectivity to diverse data sources — OT networks, PLCs, sensors, MES, ERP. Evaluate connectivity options and the complexity of integrating your specific equipment and systems.

02

Real-Time Processing Latency

The value of real-time operational intelligence depends on how quickly data from the shop floor reaches the dashboard. Evaluate end-to-end data latency from sensor reading to dashboard display.

03

Analytics Depth

Beyond dashboarding, evaluate the platform's analytics capabilities — trend analysis, anomaly detection, correlation analysis, and the ability to build custom analytics models on your operational data.

04

OT/IT Security

Operational intelligence bridges OT and IT networks, creating potential security risks. Evaluate the platform's OT security architecture — network segmentation, protocol security, authentication — before connecting any critical operational systems.

05

Scalability to Full Facility Coverage

Starting with one line or one facility is common, but the platform must scale cost-effectively to full enterprise coverage. Evaluate per-asset licensing and the total cost at your target scale.

06

Integration with ERP & MES

Operational intelligence that remains isolated from ERP and MES creates data reconciliation problems. Evaluate integration depth with your existing operational and business systems.

"RLM brought structure to a process we didn't know how to start. They asked the right questions, surfaced the right vendors, and kept us from making decisions we would have regretted."

CTO — Mid-Market Financial Services Firm

The benchmark comes first. Without a baseline, “savings” is just a number a vendor gave you.

A Sample of the AI & Automation Providers We Evaluate

AnthropicOpenAIGoogle GeminiMicrosoft CopilotObserve.AIKore.aiYellow.ai

RLM is vendor neutral. These are among 600+ providers in our evaluation set — inclusion here is not an endorsement, and we are paid by the provider you choose, not by any provider in particular. How that works →

Ready to Move on Operational Intelligence?

Start with a no-cost conversation with an RLM AI advisor — vendor neutral, no agenda, just clarity.

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