Disconnected signals
Operating evidence remains spread across controls, historians, inspections, maintenance, and production systems.
Physics AI for Industrial Operations
Real-time engineering guidance for industrial operations.
BiaTech is the company behind BiaSense, the industrial platform and reasoning layer that combines live and historical operating data with engineering physics and AI. Bia is BiaSense’s conversational advisory interface—an AI Field Engineer persona for facility, drilling, and integrity teams. Bia presents guidance; the responsible operating team decides what action to take.
Decision stateShadow modeHuman approval required
Operating marginNarrowingConstraint developing
Application areas
Choose the operating decision you need to improve.
Each application uses BiaSense differently, with workflows designed around the people responsible for the result.
For plants, process facilities, and water operations
Smart Facilities
Connect scattered operating signals to support production optimization, throughput, quality, and operating efficiency while strengthening equipment reliability.
For drilling and remote-operations teamsDrilling Intelligence
Bring hydraulics, hole cleaning, and drill-string conditions into the decision window while the crew can still respond.
For integrity, inspection, and maintenance teamsAsset Integrity
Turn inspection evidence and operating history into clearer repair, monitoring, and continued-service priorities.
The operating problem
Industrial data is abundant. Timely engineering judgment is not.
Important signals remain separated across systems, while critical analysis often depends on a few experts and arrives after the decision window has narrowed.
Delayed expertise
Engineering analysis is often performed away from the moment when the operator needs it.
Limited context
Generic predictions are difficult to use when the physical constraint and operating consequence are unclear.
What BiaSense adds
Engineering context between the data and the decision.
BiaSense evaluates equipment behavior against physical expectations and approved operating limits. Bia presents what deserves attention and explains the next decision to consider in practical language. The responsible operating team decides what action to take.
Observe
Connect live and historical data from sensors, controls, historians, inspection tools and operational systems.
Model
Organize equipment behavior against physical assets, workflows and approved operating limits.
Predict
Use physics, digital twins and machine learning to evaluate behavior, risk and possible next actions.
Advise
Return traceable, plain-English guidance with evidence and clear decision boundaries.
Works above existing industrial systems.
Runs at the edge, on-premises, or in a governed cloud environment.
Begins in advisory or shadow mode so experts can validate the guidance.
Fit and trust
Fits the operation without replacing it.
One site. One workflow. One measurable KPI.
Start with one operating decision worth improving.
Define the asset, accountable owner, available data, and current baseline. If the result is proven, the same BiaSense workflow can expand across additional assets, sites, or operations.