BiaTech Field Notes

Field notes on industrial AI in real operations.

Practical perspectives on Smart Facilities, Drilling Intelligence, Asset Integrity, physics-informed machine learning, and edge computing—for the people who must trust the evidence and own the outcome.

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Topics covered

Platform
Smart Facilities
Drilling Intelligence
Asset Integrity
How It Works
Company News

Physics-grounded. Human-reviewed. Built for operating teams.

Featured field note

Evidence, engineering context, and practical action

Industrial operator reviewing live equipment guidance beside operating machinery

PlatformFebruary 2026

Physics AI for Industrial Operations: What It Means

Physics AI combines engineering models, operational data, and machine learning to help industrial teams understand what equipment is doing, what may happen next, and what actions deserve attention.

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From the field

Latest field notes

Read by application, operating challenge, or the decision your team needs to make next.

Illustrative industrial AI team reviewing an energy-technology deployment plan beside process equipment

Illustrative imageCompany NewsAugust 2026

BiaTech Named a 2026 Rose Rock Bridge Showcase Awardee

BiaTech was named a 2026 Rose Rock Bridge Showcase awardee, creating new opportunities to advance commercialization and pilot development in Tulsa’s energy ecosystem.Read field note

Drilling operator reviewing live rig conditions and engineering guidance in a control cabin

Drilling IntelligenceAugust 2026

When Engineering Guidance Arrives Too Late, Operators Stop Trusting It

Drilling teams do not need another delayed calculation or disconnected screen. They need timely, explainable engineering guidance that reflects what is happening in the well now.Read field note

Engineer comparing an industrial equipment model with live operating data

PlatformJanuary 2026

How PIML Makes Engineering Models Faster Without Abandoning Physics

Physics-informed machine learning can make complex engineering analysis practical within operational workflows while preserving the physical constraints that give the result meaning.Read field note

Industrial edge computer connected to equipment and secure enterprise systems

PlatformApril 2025

Edge-to-Enterprise AI: Put Compute Where Industrial Decisions Happen

Industrial AI should place each workload where it makes operational sense—from equipment-side compute to secure enterprise resources—while preserving one consistent decision workflow.Read field note

Existing industrial sensors and control equipment connected to an edge AI application

How It WorksAugust 2026

Industrial AI Without a Rip-and-Replace Mandate

BiaSense is designed to work with qualified customer sensors, industrial systems, and local compute—allowing an AI initiative to begin with the infrastructure already in place.Read field note

Operator surrounded by industrial control screens receiving concise engineering guidance

How It WorksAugust 2026

Operators Need Real-Time Engineering Guidance, Not Another Dashboard

Industrial teams already have screens filled with data. The greater opportunity is to turn that data into timely engineering guidance that supports the next operating decision.Read field note

Industrial operations represented across smart facilities, drilling, and asset integrity

PlatformAugust 2026

One Reusable Physics AI Platform, Three Focused Industrial Applications

BiaSense provides a common technical foundation for Smart Facilities, Drilling Intelligence, and Asset Integrity while keeping each customer experience focused on a specific operational outcome.Read field note

Engineer comparing a physical industrial pump with its digital operating model

PlatformAugust 2026

An Industrial Digital Twin Should Advise, Not Just Mirror

A useful industrial digital twin does more than reproduce the current state of an asset. It helps people interpret behavior, evaluate risk, and consider the next action.Read field note

Field operator reviewing and approving industrial AI guidance on a tablet

How It WorksMarch 2025

Human-in-the-Loop Industrial AI: Build Trust Before Operational Dependence

Industrial AI earns trust by advising within defined boundaries, showing its evidence, and proving its usefulness in shadow mode before entering an active workflow.Read field note

Field inspector examining industrial pipe while reviewing digital inspection information

Asset IntegrityAugust 2026

From Inspection Records to Better Asset Decisions

Inspection results become more valuable when they are interpreted alongside operating history, engineering physics, and the decisions asset owners must make next.Read field note

Camera inspecting industrial pipe while an engineer reviews condition information

Asset IntegrityApril 2024

Computer Vision Is One Sensor in an Industrial Decision System

Industrial computer vision becomes more valuable when image evidence is combined with operating data, asset history, engineering physics, and human review.Read field note

Industrial supervisor reviewing facility operations in a modern control room

Smart FacilitiesAugust 2026

Your Facility Does Not Need Another Disconnected Dashboard

Smart Facilities begins with the systems a plant already has, connecting operational data with engineering context and plain-English guidance.Read field note

Operations and engineering team defining a focused industrial AI pilot

How It WorksAugust 2026

How to Prove Industrial AI Value Without Starting With a Transformation Program

A well-designed industrial AI pilot begins with one site or asset, one workflow, one subject-matter expert, and one measurable KPI.Read field note

Industrial operator comparing multiple data sources while making an operational decision

PlatformOctober 2024

Industrial Operations Do Not Have a Data Shortage. They Have a Decision-Context Problem.

The goal is not to place more data in front of operators. It is to connect the right data with engineering context at the moment a decision must be made.Read field note

Illustrative geothermal well and surface-facility infrastructure

Illustrative imageCompany NewsNovember 2024

BiaTech Completes Phase I of U.S. DOE-Supported Geothermal Research

BiaTech completed Phase I research supported by the U.S. Department of Energy to explore high-temperature, multiphase geothermal flow monitoring.Read field note

Illustrative industrial AI prototyping workspace with edge hardware and a pump test loop

Illustrative imageCompany NewsJanuary 2025

BiaTech Opens an Industrial AI Prototyping Lab at Greentown Labs Houston

BiaTech opened a prototyping lab at Greentown Labs Houston to bring software, sensors, edge computing, and industrial equipment workflows together in one development environment.Read field note

Illustrative human-led industrial inspection technology demonstration

Illustrative imageCompany NewsNovember 2025

BiaTech Showcases AI Inspection Technology at the 2025 Greentown Labs Climatetech Summit

At Greentown Labs’ 2025 Climatetech Summit in Houston, BiaTech demonstrated how computer vision, edge computing, and human review can improve industrial inspection workflows.Read field note

Illustrative industrial edge computer supporting local AI workloads beside process equipment

Illustrative imageCompany NewsMarch 2024

BiaTech Joins NVIDIA Inception to Advance Industrial Edge AI

BiaTech joined NVIDIA Inception in March 2024, gaining access to technical resources that support the development of GPU-accelerated Physics AI for industrial operations.Read field note

Illustrative industrial digital-twin prototype with a pump test loop

Illustrative imageCompany NewsJuly 2024

The 2024 Digital-Twin MVP Became the Foundation of BiaSense

BiaTech’s July 2024 digital-twin MVP established the architecture that would grow into BiaSense, a common Physics AI platform for industrial decision support.Read field note

BiaTech founder Nathaniel Hartwig in a professional portrait

Company NewsAugust 2023

BiaTech Founded to Bring Physics AI to Industrial Operations

BiaTech was founded in August 2023 around a clear conviction: industrial teams need real-time engineering guidance where consequential work happens, not another disconnected dashboard.Read field note

From perspective to practice

See how approved data becomes human-reviewed guidance.

Follow the BiaSense operating loop from connected evidence through physics-grounded reasoning, expert validation, and practical advice.

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Bring us one decision

Start with the workflow that matters now.

Tell us about the asset, site, rig, or process; the data available; and the result your operating team needs to improve.

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Start with a qualification call and focused data-path review.