KLA vs Onto Innovation
Relationship
Named as a competitor in KLA's own 10-K; both are AI-enabled semiconductor-manufacturing-equipment vendors.
3 shared capabilities — Across all their products, both list data analysis, industrial automation and semiconductor manufacturing equipment.
Ludbee capability tags · every product each company sellsDifferent layer — Onto Innovation ships application, not the same layer.
Ludbee product recordsNamed in filing — “including companies such as Applied Materials, Inc., ASML Holding N.V., Hitachi High-Tech Corporation, Lasertec, Inc. and Onto Innovation, Inc.”
sec.gov · checked 2026-10-11Buy data-centre AI compute — Rivals on this job — Equip a data centre to train and serve models — accelerators bought as chips, cards, servers or rack systems, or rented as dedicated cloud capacity.
Ludbee needs vocabulary · the scope on the sourced edgeAligned comparison
Capability overlap
Shared · 3
Not verified for Onto Innovation · 1
Recorded for KLA. Onto Innovation’s product records say nothing either way — a missing record is not a missing capability.
Onto Innovation has no capability KLA lacks, among the 3 recorded here.
Products, side by side
Hand-checked pairing
KLA
No shared stack layer with the other side.
Onto Innovation
No shared stack layer with the other side.
No counterpart
KLA sells these in a stack layer with no product recorded for Onto Innovation yet — nothing on the other side to compare them against.
Hardware
Laser-scanning patterned-wafer inspection system for advanced logic and memory fabs, built around DefectWise, a deep-learning algorithm that separates defects of interest from pattern noise and nuisance defects inline to speed up process-excursion diagnosis.
E-beam patterned-wafer defect inspection system that finds defects other inspectors miss, using KLA's SMARTs deep-learning algorithms to separate defects of interest inline at leading logic and memory fabs.
Onto Innovation sells these in a stack layer with no product recorded for KLA yet — nothing on the other side to compare them against.
Application
Defect-classification software that combines deep learning, a dynamic library of real defect examples and a multi-engine mode to classify wafer defects inline, flagging low-confidence defects as unknown and cutting manual review by over 70%.