Engineering & AI
We develop the process.
Not just run it.
Advanced packaging built on data and AI-assisted process control — one engineering team from design review through volume, on US soil.
/ SPC-controlled / MIL-STD when required / ITAR-aware / US-soil
In-house die attach & data-driven process control.
Anyone can run a recipe.
The hard part is developing one.
Most shops can bond a die or reflow a bump. The value is getting a new process to work — fast, repeatable, and documented — before it costs you a tapeout.
We treat process development as an engineering problem backed by data, not trial and error. Define the objective, build a test vehicle, run the DOE, validate with real metrology, and document what we learned.
AI-assisted iteration reduction
Data decides. Engineers sign off.
We aggregate process, inspection, metrology, and test data across every build, and use AI as a decision-support layer to surface drift and correlations faster than eyeballing ever could.
AI narrows the search. An engineer owns the call — every process adjustment stays traceable and tied to manufacturability and reliability.
- 01Aggregate process, inspection, metrology & test data
- 02Trend analysis to catch drift and variation early
- 03Correlate process parameters with yield and defect modes
- 04DOE planning, refinement, and prioritization
- 05Faster root-cause and failure-mode identification
Fewer trial-and-error iterations · faster convergence on stable process windows · lower cost and schedule risk · higher confidence before production-intent.
Proof, from real builds
Closed-loop design of experiments
SPC-driven process control
Inspection automation on every build
Full design rules, process detail, and build data available under NDA.
How we develop
A framework, not a guess.
Hybrid Agile cycles with engineering phase gates.
Rapid learning with traceability and manufacturability discipline — so early risk gets retired before scale-up, not discovered after it.
FAQ
Common questions.
Do you just run recipes, or develop the process?
We develop it. Most shops can run an established recipe; the value is getting a new process to work — fast, repeatable, and documented — before it costs you a tapeout. We treat process development as an engineering problem backed by data, not trial and error.
How is AI actually used here?
As decision-support, not autopilot. We aggregate process, inspection, metrology, and test data across every build and use AI to surface drift and correlations faster than eyeballing can. An engineer owns every call — each adjustment stays traceable to manufacturability and reliability.
Does AI replace your engineers?
No. AI narrows the search; engineers sign off. The goal is fewer trial-and-error iterations and faster convergence on a stable process window, not removing human judgment.
What do we get out of it?
Fewer iterations, faster convergence on a stable process, lower cost and schedule risk, and higher confidence before production-intent — with the data trail to back each decision.
Process More.
Bring us the process
that isn't working yet.
One team, design review through volume. Request a capability brief for design rules, full process detail, and build data under NDA.
/ US-soil / ITAR-aware / MIL-STD