Machine data is difficult to use.
Machine readings need to be collected, processed and monitored before engineering teams can use them for analysis.
Domain depth / Semiconductor
Data engineering for semiconductor manufacturing.
UTIS provides data engineering for semiconductor manufacturing, including machine telemetry, Azure Databricks pipelines, factory analytics, enterprise reporting and scientific AI. We have been a preferred engineering vendor to a global semiconductor company since 2019. Our engineers work on the systems that turn operational data into usable information, with validation and support requirements defined for each engagement.
Semiconductor data
From machine signals to usable data.
- Machine sources
Signals, logs and source systems
- Data engineering
Processing with validation
- Engineering use
Tables, reporting and analysis
Your priorities
Problems we help solve
These are common reasons to bring UTIS into the work.
A manufacturing system cannot change in isolation.
Reporting, legacy tools and source-system restrictions can affect the timing and scope of a technology change.
More processing increases cloud cost.
Growing data volumes require attention to both the quality of the results and the resources used to produce them.
Our contribution
Where can UTIS help semiconductor teams?
Make machine data accessible
Support existing streaming platforms, connect additional sensors and consolidate monitoring so teams can inspect current machine data.
Lakehouse and pipeline fleets
Databricks deployment standardization, incremental loading, cost optimization and new pipeline delivery.
Support factory analysis and reporting
Build browser-based analysis, statistical alerting and reporting that can continue when changes to a source system are restricted.
Validate AI for engineering work
Interpret legacy engineering documents, demonstrate machine-learning delivery frameworks and test scientific simulations on an existing GPU platform.
Project experience
Examples of relevant results
Each result describes a specific engagement and retains its original source and scope.
Since 2019
Preferred vendor since 2019
Engineering delivery for a global semiconductor company.
Documented client relationship
100%
Existing streaming components in one health view
UTIS operates and extends the existing stream, rebuilt component health monitoring and supports machine onboarding and self-service access.
Documented platform operation and monitoring. The case also reports existing-platform latency as context, not a UTIS-created speed improvement.
Read the case~57%
Lower average daily compute cost
Eleven machine-log pipelines, first days after migration compared with a five-month baseline.
How we measured it: platform-reported daily compute cost, averaged over the baseline period and the initial post-migration window; the same datasets continued to reach users throughout.
Read the case~10×
Faster scientific simulation
A scientific simulation reproduced the reference physics on H100 GPUs and ran ~10× faster than the standard environment.
validated proof of concept
Read the caseWorking together
Scope one manufacturing-data change
Bring the workload and reference
Start with the machine-data flow, report or analysis job you want to improve, its users and an example of the current output. Identify access and change restrictions.
Agree the first deliverable
Select a bounded pipeline change, monitoring improvement or validation exercise. Define UTIS’s ownership, client dependencies and the evidence needed for acceptance.
Compare before expanding
Agree reference outputs, the processing window and validation checks before work begins. Review the result with the engineers who use the data, keeping benchmarks distinct from production adoption.
Plan the operational handover
Name the operating owner and agree documentation, alerting, support coverage and cutover criteria. Any ongoing service commitment belongs in the engagement scope.
Explore the expertise
Choose your next step
Go deeper into the work, explore an example or review how to engage UTIS.
Databricks engineering
Review pipeline work, validation methods and the scope behind reported results.
Cloud & DevOps
Explore platform engineering, deployment and operational responsibilities.
Vendor review
Discuss confidentiality, access, relevant references and engagement requirements.
Before we start
Frequently asked questions
What to expect when you work with UTIS.
Can UTIS meet our supplier and security requirements?
We review security, access, staffing and supplier onboarding requirements with you before agreeing an engagement. The scope and working arrangements depend on the work and the requirements your team needs us to meet.
Are all case-study benefits already realized?
No. Each case states its stage. Factory alerting includes one measured incident alongside projected benefits; the scientific AI speedup is a validated proof of concept. Those qualifications stay with the results.
Can procurement contract directly with UTIS?
Yes. Our anchor clients contract with UTIS directly. We can work under your master services agreement or ours. Client references require permission and appropriate confidentiality arrangements.
Meet with UTIS
Book a meeting.
Choose a preferred time for a 30-minute conversation about your project or hiring needs.
Choose a preferred time
Book a meetingUTIS will review your preferred time and confirm the meeting by email.