NeuralChain
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Industries

We focus on advanced
technology industries.

Some results can only come from a team fluent in process, equipment and materials terminology. We narrow to five industries to buy depth.

See it by industry Industry consultation
Value Chain One chain, from material to finished product
Material Properties · microstructure
Equipment Precision equipment · components
Process Deposition · etch · inspection
Product Semiconductor · display
Volume production Automated lines
Verticals

Every industry
stalls somewhere different.

The same product goes in, but the starting point and the first priority depend on how the industry is built.

Semiconductor
Semiconductor

As geometries shrink, the volume of evidence needed for prior-art review and process-condition decisions rises sharply — while fab data stays scattered across individual tools.

IP-R&D prior art · design-around review
Tracing the link between process conditions and defects
Unifying tool logs with lot history
Display
Display

With larger panels and new materials arriving together, it is hard to judge in advance how a change in deposition or inspection conditions will hit yield.

Reading technology trends and the patent landscape for new materials
Linking deposition-condition change history to yield
Attributing inspection defect types to specific equipment
Advanced materials
Advanced Materials

Experimental data and literature accumulate with individual researchers, so the search history behind compositions and process conditions never stays with the organisation.

Finding composition candidates from papers and patents
Accumulating experiment history and the evidence behind decisions
Working back from a customer's required properties
Equipment · components
Equipment & Components

Specifications differ by customer, so design assets scatter across projects and finding how a past case was handled takes time.

Unified search across design assets and past responses
Matching component specifications to customer requirements
Tracing the cause of delivery and quality issues
Advanced manufacturing
High-Tech Manufacturing

Lines are automated, but equipment, quality and planning data sit in separate systems, so no one sees the whole flow on one screen.

Connecting equipment signals to actuals
Live visibility of plan versus actual
Accumulating manufacturing data fit for AI training
Domain Depth

Narrow the scope
and depth follows.

That is why we do not take on finance, retail or the public sector. The conceptual systems of five industries go straight into the ontology.

Process concepts
Equipment · parameters
Defects · quality
IP · literature
Semiconductor
Core
Core
Core
Core
Display
Core
Core
Core
Applied
Advanced Materials
Applied
Applied
Applied
Core
Equipment & Components
Applied
Core
Applied
Applied
High-Tech Manufacturing
Core
Applied
Core
Extended
Reflected in the ontology Each industry's conceptual system, defined as a relational structure

Start with a problem
from your own industry.

We set the starting point against that industry's processes and data structures.

Request an industry consultation See it by industry again