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ARRAYMATIC

ArrayMatic Technologies

B-23, B Block, Sector 63, Noida, Uttar Pradesh 201301

[email protected]

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HomeIndustriesConsumer ElectronicsAI for Product Lifecycle Management

Consumer Electronics

AI for Product Lifecycle Management

Data platforms that track consumer electronics from design through post-sale — capturing field performance, return reasons, and firmware version data to drive continuous product improvement.

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Industry overview

Product lifecycle analytics platforms for consumer electronics that connect design, field performance, return data, and firmware version telemetry — giving product teams the closed-loop feedback needed to improve successive hardware revisions.

At a glance

  • Field failure telemetry aggregation by component and firmware version
  • Return reason classification and root cause analysis
  • Firmware version performance comparison across device populations

Consumer electronics product teams make decisions for the next hardware revision with limited visibility of how current products actually perform in the field. Return reasons are logged at the retail level with insufficient detail. Field failure patterns are not correlated with component batches or firmware versions. Customer feedback is sampled rather than systematically captured. A connected PLM platform closes these gaps.

What we build

We build product lifecycle data platforms that aggregate field failure telemetry, return reason data, firmware version performance, and customer feedback into a unified product health view. Failure pattern analysis identifies whether issues correlate with specific component batches, manufacturing dates, or firmware versions — enabling targeted remediation rather than blanket product recalls. EOL planning analytics model when a product generation transitions from growth to decline to inform discontinuation timing and service parts planning.

Key capabilities

What we deliver

Engagements are scoped to your business context — these are the core capabilities we bring to consumer electronics clients.

Field failure telemetry aggregation by component and firmware version

Return reason classification and root cause analysis

Firmware version performance comparison across device populations

Component batch quality correlation with field failure rates

Customer feedback aggregation and theme extraction

EOL planning analytics and service parts demand forecasting

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