About InflexionPoint

At InflexionPoint, we help companies harness the power of automation and data to make better decisions and operate more efficiently, safely, and effectively.

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DataOps at the Edge

The Foundation for Trustworthy AI

Industrial DataOps

Building a Solid Industrial DataOps Foundation

Your industrial data lives in rigid, fragmented silos (e.g., PLCs, SCADA systems, historians). Transforming this into usable data for modern enterprise systems has historically required heavy custom coding and scripting, making it difficult to scale smart manufacturing initiatives. InflexionPoint designs, deploys, and manages the industrial data foundation that makes AI trustworthy — from sensors and control systems through edge DataOps, cloud landing zones, and managed AI operations — to enable:

  • Predictive maintenance
  • Quality prediction
  • Energy optimization
  • OEE and throughput
  • Operator copilot
  • OT cybersecurity

Why Industrial AI Projects Stall Before They Scale

Most failures are not caused by model quality — they are caused by data foundations that cannot be trusted or operated. The fix is a trustworthy data foundation: governed at the instrument, contextualized at the edge, operated for life. And, equally important, AI needs lifecycle support, including model monitoring, drift detection, retraining, and incident playbooks.

Signal Ambiguity

Tags are inconsistent, units are missing, calibrations drift, and timestamps are not normalized.

Context Gaps

Raw time series lacks asset, product, batch, work order, and maintenance context.

Integration Sprawl

Point-to-point links between PLCs, SCADA, historians, MES, and cloud become brittle.

Lack of Security

Missing capabilities: zones, conduits, DMZs, least privilege, and monitored remote access.

WHERE TO START

Start with an AI Readiness Assessment

Is your operation AI-ready? Let us help you find out, with a fixed-scope engagement to map your instruments, data, and use cases — and a clear plan to build the foundation that makes AI trustworthy.

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The Hidden Cost of Cloud-First Architectures (and Why Edge Wins)

A typical enterprise with, say, ten sites and 50,000 tags per site sampling at a rate of once per second, generates billions of records per day and terabytes of data per year. The result: cloud costs become disconnected from business value. The “cloud” is an excellent platform for enterprise analytics and AI. However, Fabric, OneLake, etc were not designed to be the primary repository for every raw industrial signal generated by a manufacturing enterprise. There is a better way. Create value at the edge and move only what matters.

The Problem with Cloud-First

In a cloud-first scheme, every signal is collected, even if nobody uses it. Then, the cloud operators want to contextualize data once it reaches the cloud. The challenge is that industrial data is not born contextualized. Customers end up spending millions reconstructing context after the fact.

Why Edge Wins

Speed is important, but precision is paramount. Our bioinformatics and process automation solutions provide the insights and control you need to drive breakthroughs and deliver effective treatments.

A Data Model That Survives Change

Most manufacturers have no idea how to operate 100-500 edge nodes. They know how to buy them. They do not know how to govern them. The question to ask is: How do I create a unified data model that survives MES replacements, ERP changes, acquisitions, AI initiatives, cloud migrations and plant modernization? The answer, delivered by InflexionPoint is:

  • Industry standards (ISA-95, ISA/IEC 62443) applied as durable data models
  • Wide-ranging integration across PLC, SCADA, historian, MES and cloud
  • OT governance programs — the tools and services to maintain these systems over time
  • A modern computer software assurance (CSA) validation strategy for regulated environments
  • Cybersecurity solutions designed for hybrid OT/IT architectures
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Have questions?
We have answers.

Do you have a Digital Transformation initiative? Need to upgrade your automation and controls systems? Wondering how you can become more data-driven? Let's talk.

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