Can the platform run in our private cloud?

Yes. Everything ships as Helm charts and Terraform modules — VPC, on-prem, or air-gapped deployments are all supported.

How do you avoid alarm fatigue?

Models learn from your historical false positives and alerts ship with confidence scores and explainable drivers.

How quickly do we see results?

Most plants see meaningful predictive value within 6–10 weeks of go-live, with ROI realized within the first year.

Manufacturing / Predictive Maintenance Dashboard

Predictive Maintenance Dashboard

We engineer AI-powered predictive maintenance platforms that fuse vibration, thermal, and SCADA telemetry into actionable, plant-floor diagnostics — and route them straight into your CMMS.

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35%

Average reduction in unplanned downtime

100k+

Sensor channels per deployment

4–6 mo

Typical early-warning window before failure

Trusted by global innovators

Industry Overview

Predictive Maintenance Dashboard: Engineered End-to-End

Modern factories generate more sensor data in a week than most operations teams can review in a year. We build platforms that distill that data into a focused, prioritized list of equipment health issues — without flooding maintenance teams with noise.

Industry Challenges

What Stops Most Teams From Solving This Today

Common friction points we hear from manufacturing teams scoping this kind of platform.

Alarm Fatigue: Threshold-based SCADA alarms produce thousands of weekly alerts that floor teams learn to ignore.
Disconnected Workflow: Diagnostics rarely flow automatically into work orders, parts ordering, or crew scheduling.
Legacy Equipment Blindness: Older PLC-based machines don't expose modern telemetry without specialized adapters.
Scaling Pain: Pilot dashboards built in Power BI or Excel don't survive scaling from one line to a whole plant.

Our Approach

Our Engineering Approach

We engineer for the operational reality — not the demo.

Multi-Modal Sensor Fusion

Vibration, thermal, current, and SCADA signals combined into a single asset health score with explainable drivers.

Edge Inference

Lightweight ML at the line keeps latency low and avoids shipping raw waveforms upstream.

Closed-Loop CMMS

Diagnoses become pre-filled work orders in Maximo, SAP PM, or Infor with parts and procedures attached.

Capabilities

Production-grade features the platform ships with from day one.

Equipment Health Scores

Per-asset 0–100 score with trend, drivers, and recommended action.

Failure Mode Classification

Identify the specific failure — bearing wear, motor drift, gear pitting — not just 'anomaly'.

Edge Inference

Industrial-grade edge boxes run inference and stream features upstream.

Plant-Wide Heatmaps

Visualize line and plant health at a glance with drill-down to single assets.

Auto Work Orders

Diagnoses become pre-filled CMMS work orders with parts and procedures.

Alarm Suppression

Models learn from prior false positives, slashing low-value alerts.

Mobile Field App

Tablet-friendly dashboards purpose-built for floor maintenance crews.

Reporting

Reliability KPIs, MTBF, MTTR, OEE — all from one source of truth.

How It Works

Reference Architecture

How data and decisions flow end-to-end.

Plant Edge

PLC, sensor, and SCADA data normalized at industrial edge gateways.

Stream Processing

Feature extraction, drift detection, and first-line ML at the edge.

Cloud Lakehouse

Bronze/silver/gold layers with full event history for retraining and audit.

Model Pipeline

MLflow-tracked retraining with canary promotion and rollback.

Operator Apps

Web and mobile apps for floor managers, reliability engineers, and crews.

Engineering Stack

Technology Stack

A pragmatic stack chosen for reliability, speed, and ease of operation.

Edge & OT

OPC-UAModbusMQTTIgnitionLinux RT

Data

TimescaleDBKafkaIcebergDuckDB

ML

PyTorchscikit-learnONNXMLflow

Apps

Next.jsReact NativeGraphQLTailwind

Infra

KubernetesVaultTerraform

CMMS

MaximoSAP PMInfor EAM

Measured Impact

Quantified outcomes from production deployments.

35%

Reduction in unplanned downtime

20%

Reduction in maintenance cost

73%

Lower false-positive alerts

5×

More assets per reliability engineer

Global Automotive Tier 1 Plant Reliability

An automotive supplier ran into chronic press-line failures driving multi-million-dollar downtime events. We deployed an edge-to-cloud predictive platform across two pilot plants.

Within nine months the platform predicted 47 high-impact failures with average lead time of 11 weeks, reducing unplanned downtime by 35% and reclaiming $9M in annualized production capacity.

Case Study

Global Automotive Tier 1 Plant Reliability

Use Cases

Where This Earns Its Keep

Common deployment patterns we see across customers.

Press Line Reliability

Vibration and current signature analysis on stamping presses.

Robotic Cell Health

Servo and harmonic drive condition monitoring.

Compressor Monitoring

Plant-wide compressed air system reliability.

Conveyor Health

Roller bearing and motor health on long conveyor systems.

HVAC Optimization

Plant HVAC efficiency and reliability monitoring.

Energy Submetering

Identify hidden energy losses tied to equipment health.

Integrations

Integrates With Your Existing Stack

We connect to the systems your teams already know.

PLC / SCADA

Rockwell AutomationSiemens TIA

SCADA

GE iFIXIgnition

CMMS

IBM MaximoSAP PM

Warehouse

Snowflake

Compliance-First Development Services Backed by Global Standards

We build secure, scalable products designed for privacy, interoperability, and regulatory readiness from day one across every sector we serve.

Service Organization Control 2

Verified controls for security, availability, and confidentiality of enterprise data systems.

Information Security Management

Adhering to the international gold standard for managing information security risks.

Quality Management Systems

Ensuring consistent quality in software delivery and operational process optimization.

Our Edge

Why Global Leaders Choose Us

We combine deep technical expertise with industry-specific knowledge to deliver solutions that aren't just functional, but transformational.

Enterprise-Grade Security

We implement rigorous security protocols and compliance standards (HIPAA, GDPR, SOC2) across all industrial solutions to protect sensitive data.

High-Performance Scaling

Our architectures are built to handle massive data loads and user bases, ensuring seamless performance whether you're serving ten or ten million.

Accelerated Time-to-Market

Leveraging our suite of internal tools and proven frameworks, we reduce development cycles and get your product to market 40% faster.

Embedded AI Integration

Beyond simple wrappers, we build deep-learning integrations and predictive analytics directly into the core of your industry-specific workflows.

Engagement Model

Predictable, structured delivery from kickoff through long-term ownership.

Discovery & Scoping

We map the existing systems, constraints, and stakeholders to scope a focused 8–12 week first delivery.

Architecture & Pilot

A working slice on a representative environment — proving the data flow end-to-end before scaling.

Production Engineering

Hardened services, observability, access controls, and audit logging go live behind your IAM.

Operate & Iterate

We stay on as the embedded engineering team — closing tickets, tuning models, and shipping new value.

Voices of Success

We don't just build products; we forge lasting partnerships. See how we've helped industry leaders transform their vision into technical reality.

"I can clearly see how Agnotic has a unique way of handling end-to-end development. They are always active on quick chat and provide support quickly."

Aaron Phelan

Founder, Benchmark

"Agnotic is the best technical team we evaluated. Their engineering excellence made our work dramatically easier and allowed us to stay focused on what matters most for maternal care outcomes. They took full ownership of the technical execution, and we are always happy to continue working together."

Kim Smith

Founder, My Lauren

"Agnotic combines deep technical expertise with strong domain knowledge. They understand the business context, anticipate challenges, and make collaboration smooth and effective."