Scriptix
AI & Software Development for Industrial & Manufacturing
Industrial software has to work alongside equipment that was never designed to talk to modern systems, and unplanned downtime here isn't an inconvenience: it's lost production.
What We Cover
What This Usually Means
Most industrial and manufacturing environments run a mix of modern IT systems and much older operational technology (OT): PLCs, SCADA systems, sensors, all built for reliability, not connectivity. Getting production data out of that equipment and into something a modern application can use is usually the first real engineering problem, before any dashboard or AI model matters.
Downtime has a direct, measurable cost on a production line in a way it often doesn't for a typical web application. That's why predictive maintenance (catching equipment issues before they cause a stoppage, rather than after) is one of the highest-value places to apply data and AI in this space.
Safety and process compliance requirements also shape what "done" looks like: software touching production equipment usually needs a higher bar for testing and fail-safes than a typical internal tool, because a bug here can mean more than a bad user experience.
How Our Services Apply
Data Engineering
Getting sensor and equipment data out of legacy OT systems and into a usable pipeline.
AI Automation
Predictive maintenance models that flag equipment issues before they cause downtime.
Custom Software Development
Adapter layers and dashboards that bridge legacy equipment and modern software.
Cybersecurity Consulting
OT/ICS security assessment for systems that were never designed to be network-connected.
Curious how our approach translates across industries? See illustrative scenarios →
Common Questions
Can you work with our existing SCADA or PLC systems? expand_more
In most cases, yes, via standard industrial protocols like Modbus or OPC-UA where the equipment supports them. We assess what your specific systems can actually expose before proposing an integration approach.
How much sensor data do we need before predictive maintenance is worthwhile? expand_more
Enough historical data to cover a few real failure events, ideally. If you don't have that yet, the first step is usually just building the data pipeline and collecting cleanly for a while before a model makes sense.
Do you handle software for safety-critical systems? expand_more
We build monitoring, analytics, and integration software around industrial systems. For control software directly governing safety-critical functions, that typically requires certified processes and specialized expertise beyond general software development, so we'll tell you honestly if a project falls into that category.
Working with legacy industrial systems?
Tell us what equipment and data you're working with, and we'll help you think through what's realistic.
Talk to Us