Applied AI, automation, supply chain and energy

We turn operational data into systems that run better.

Industrial and manufacturing operations already produce the data that explains them. We build the models, automation and software that act on it, across AI, digital systems, supply chain and energy. Digital work is delivered remotely. On-site engineering covers Wisconsin, Illinois and Minnesota.

Contact us What we do
How the work fits together Data › models › outcomes

Two ways we work

Delivered remotely. Boots on the floor where it matters.

Most of what we build ships remotely. Energy work is the exception, because nobody can audit a compressor over a video call. We are honest about which one your problem needs.

Remote delivery

AI, automation and supply chain

Production systems at a fraction of the cost of a large consultancy.

We build what the problem actually calls for. Classical machine learning where it wins, deep learning where the signal demands it, and generative AI or agentic systems where the work is language and documents. No method is chosen because it is fashionable.

  • Forecasting, anomaly detection and predictive maintenance
  • Deep learning on sensor, vision and time-series data
  • Generative AI and agentic workflows for documents and operations
  • Automation and control system integration
  • Supply chain visibility, planning and risk models
Talk to us about a build

On site · Wisconsin, Illinois, Minnesota

Energy performance engineering

Savings measured against a metered baseline, never estimated from a spreadsheet.

Someone walks your floor, meters your equipment, reads your drawings and argues with your utility invoices. Compressed air, motors and drives, process heat, demand charges, power factor, scheduling. Every measure is costed, then verified once it is in.

  • In-person walkthroughs and equipment metering
  • Facility and process energy audits
  • Utility tariff, demand charge and power factor analysis
  • Measurement and verification against a real baseline
  • Electrification and decarbonization roadmaps
Talk to us about a site

Services

Four practices, run as one

Most operators do not need another dashboard. They need people who can read the data, argue with the drawings, and then own what gets built. These practices are usually sold separately. We run them together, because the problems do not respect the boundaries.

Applied AI and machine learning

Old-school ML, deep learning or agentic AI, whichever actually wins.

  • Forecasting and demand prediction
  • Anomaly detection on sensor and meter data
  • Deep learning for vision, signals and time series
  • Generative AI agents for specs, tenders and manuals
  • Optimization models for scheduling and dispatch

Deliverables Working models · Data pipeline · Handover docs

Automation and digital systems

Connect the plant floor to something that can act on the data.

  • SCADA, BMS and historian data pipelines
  • Control system and PLC integration
  • Workflow and back-office automation
  • Metering strategy and instrumentation
  • Reporting built on your own data, not ours

Deliverables Integration plan · Live data flow · Specifications

Supply chain systems

Specify well, source well, and know the lead times.

  • Demand and inventory forecasting models
  • Lead-time and single-source risk mapping
  • Supplier and logistics visibility tooling
  • Equipment specification and vendor due diligence
  • Total cost of ownership modeling

Deliverables Planning model · Vendor scorecard · Risk map

Energy performance

Find the load, price it, then prove the saving.

  • Industrial and process energy audits
  • Tariff, demand charge and power factor analysis
  • Measurement and verification
  • Decarbonization and electrification roadmaps
  • Energy management system support

Deliverables Costed measure list · Verification plan · Baseline model

How we work

Baseline, model, implement, verify

The order matters, so we number it. Skipping the baseline is the most expensive decision an AI or energy project can make. Without it, nothing downstream can be proven, and every result becomes an opinion.

  1. 01

    Baseline

    The data you already have: meters, control systems, records, drawings, documents. We establish what is actually happening, not what the nameplate or the spec says.

    Typically 2 to 3 weeks

  2. 02

    Model

    A calibrated model of the problem, whether that is loads and tariffs or demand and lead times. Every option gets a cost, a benefit and a stated confidence level.

    Typically 2 to 4 weeks

  3. 03

    Implement

    We build the software, write the specifications, run the tender, and sit on your side of the table through delivery and commissioning.

    Scope dependent

  4. 04

    Verify

    Measured against the baseline we started from. Model performance and energy savings alike are reported from data, not asserted.

    12 months of reporting

In development

Software tools, coming soon

The same problems keep recurring across the operations we work with, so we are productizing the parts that generalize. These are in active development rather than available today. If one is useful to you, say so and we will keep you posted.

In development

Operations copilot

An agentic assistant that reads your specifications, manuals and tickets, and answers the questions your team currently digs through PDFs to solve.

In development

Load and demand intelligence

Continuous monitoring over interval and sensor data, flagging drift, anomalies and avoidable demand peaks before they show up on an invoice.

In development

Supply chain risk monitor

Lead-time and single-source exposure tracked continuously across your vendor base, instead of rediscovered during the next shortage.

Register interest in early access

Why us

Years of it, in the disciplines that matter here

Enetrion is built on long experience across artificial intelligence, digital systems, automation, supply chain and energy. That combination is the point: the people building your models are the same people who understand the plant the data came from.

  • AIMachine learning, deep learning and generative or agentic systems
  • SystemsDigital platforms, integration and industrial automation
  • Supply chainForecasting, sourcing strategy and lead-time risk
  • EnergyIndustrial audits, tariffs, demand management and verification

Working together

Three ways to start

Discovery

A short, fixed-scope look at the data you already have, ending in a written view of what is worth building and what is not.

Duration
2 to 6 weeks
Basis
Fixed fee
Best for
A first honest answer
Start a discovery

Project

Scoped delivery of AI, automation, supply chain or energy work, from proof of value through production and handover.

Duration
1 to 12 months
Basis
Fixed fee or milestone
Best for
A committed plan
Scope a project

Retained advisory

Ongoing engineering and data capacity alongside your team, drawn down as you need it.

Duration
Rolling
Basis
Monthly
Best for
Portfolios and multi-site
Discuss a retainer

Where we work

Industries we serve

Operations complex enough that the data is worth modeling, and large enough that a percentage point is a real number on the P&L.

Stamping presses on a manufacturing plant floor

Manufacturing and process

Scheduling, quality, predictive maintenance, compressed air and process heat.

Aerial view of a processing plant with storage spheres and tanks

Heavy industry and utilities

Asset telemetry, thermal systems, cogeneration, high-voltage distribution.

Shipping containers and gantry cranes at a port

Logistics and distribution

Demand forecasting, lead-time risk, warehouse loads, fleet electrification.

Solar array with wind turbines behind it

Renewables and grid

Generation forecasting, curtailment analysis, storage sizing, connection studies.

Common questions

Questions we get asked first

What does Enetrion actually do?

We build applied AI, automation, supply chain and energy systems for industrial and manufacturing operations. In practice that means taking the data an operation already produces, from meters, control systems, ERP records and documents, and turning it into models and software that change how the operation runs.

What kind of AI do you build?

Whatever the problem calls for. Classical machine learning for forecasting and anomaly detection, deep learning for signals and vision, and generative AI or agentic systems for document and workflow automation. We pick the cheapest method that solves the problem, not the most fashionable one.

Where do you work?

AI, automation and supply chain work is delivered remotely. On-site energy engineering, which needs someone physically walking the plant, covers Wisconsin, Illinois and Minnesota.

How do you handle energy savings claims?

Every measure is verified against a metered baseline rather than estimated from a spreadsheet. We will not quote you a percentage before we have seen your data, because a number produced that way is not worth anything.

How does an engagement usually start?

Usually with a short scoped discovery: we look at the data you already have and tell you whether there is a project worth running. If there is not, we say so.

Start with the data you already have.

Whether the question is a model, an integration, a supply chain or a utility bill, it is usually enough to tell us what you have and what is going wrong.

Contact us

Get in touch

Tell us what you are working on

A short note is enough to start. If we are not the right people for it, we will say so.

  • Emailsupport@enetrion.com
  • DigitalRemote
  • On siteWisconsin, Illinois, Minnesota
  • ResponseWithin two business days