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Turning reference designs

And AI models into viable products

Technical excellence in silicon is necessary, but not sufficient for OEM adoption. Neprion makes reference designs showcase-ready and AI models field-validated.

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From technical performance to validated market readiness

For semiconductor companies, the path from technically superior silicon to broad OEM adoption runs directly through reference design quality. OEMs evaluating a platform for an AI wearable program need demonstrated, validated performance in a real product form factor, under real operating conditions. AI players at the model and application layer need to demonstrate scenario-based validation data, translating lab performance to field performance.

Neprion’s engineering depth across custom silicon, product engineering, and real-world validation makes is a proving ground for both silicon players and AI players. The validation frameworks we apply in both settings results in a stronger technical story, faster OEM evaluation cycles, and a reduced risk profile to secure adoption wins.

Showcase-ready reference designs

A reference design that has been through integrated validation, with AI inference performance, power, and thermal trade-offs, and real-world reliability all characterized, is a fundamentally stronger OEM sales asset. Neprion validates reference designs against the criteria OEMs use to make adoption decisions, not against internal silicon specifications alone. 

  • Custom silicon engineering and validation aligned to wearable product requirements 
  • AI inference performance characterization under real power and thermal constraints 
  • Reference design validation that generates OEM-facing performance evidence 
Platform enablement and OEM proliferation

Getting silicon or AI technology designed into one OEM product is a start. Scaling adoption across multiple OEM programs requires technology onboarding support that goes beyond standard documentation. Neprion's platform enablement services help silicon and AI players efficiently and repeatedly extend their technology into OEM products. 

  • Technology onboarding for OEMs integrating a new silicon platform or AI stack 
  • System adaptation and integration support tailored to the OEM's specific product concept 
  • Engineering expertise that accelerates OEM evaluation cycles 
Real-world AI validation

AI models that perform well in controlled environments routinely encounter edge cases in real products that were not visible in benchmarking. Neprion's AI validation covers the scenarios that actually matter for wearable deployment—ambient noise, motion, outdoor conditions, multi-device coordination, and battery-constrained inference—generating the field evidence that reduces risks for OEM adoption. 

  • Scenario-based AI model validation across real-world environmental conditions 
  • Latency, accuracy, and battery drain characterization under actual usage patterns 
  • Multimodal AI validation covering voice, gesture, and visual inputs in field conditions 
  • AI performance benchmarking across platforms for comparative evaluation support 
Custom silicon for wearable applications

Where standard silicon platforms do not fully address the power, thermal, or inference requirements of a specific AI wearable application, Neprion's custom silicon design services enable derivative silicon development optimized to those constraints, with validation built into the development cycle from the start. 

  • Custom and derivative silicon design for AI wearable form factors 
  • Co-design of silicon and validation requirements to prevent late-stage performance surprises 
  • Silicon validation integrated with product and system validation for full-stack confidence 

Our services

Custom and derivative silicon design and validation for AI wearable applications, with power, thermal, and AI inference requirements addressed as a co-design challenge. Validation is integrated into the silicon development cycle, so performance evidence is available before OEM evaluation begins.

Field validation of AI models across the real-world conditions that wearable products encounter in use. Covers accuracy under ambient noise and environmental variation, latency under battery-constrained inference, and cross-platform performance benchmarking. Generates the evidence base that supports OEM and platform company adoption decisions.

Technology onboarding and system integration support for OEMs adopting a silicon platform or AI stack, going beyond standard documentation to hands-on integration engineering. Accelerates OEM evaluation cycles and reduces the friction that stalls adoption between proof-of-concept and design win.

System hardening based on hardware-backed security, penetration testing, and privacy compliance engineering for AI wearable platforms. Addresses the security requirements that OEMs and platform companies increasingly treat as a design-in requirement.

CASE STUDY

Smart Glasses Evolution

Learn how your team leveraged Neprion to validate their AI wearable platform and accelerate time-to-market.

Read Case Study

Talk to our leaders

Connect with our experienced team who bring years of wearable innovation to every project.

Tinku Malayil Jose

Tinku Malayil Jose

Head of Technology Office, Hi-Tech

At Quest Global, Tinku transforms cutting-edge engineering into consumer-ready innovations for the future. With experience across consumer electronics, smart wearables, automotive, and IoT, he has partnered with leading global tech companies to launch category‑defining products. He bridges technical feasibility and commercial viability, and currently pioneers scalable, market‑ready AI and AR/XR solutions that redefine industries. His leadership guides global teams through complex productization journeys from concept to scale worldwide.

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Arvind Singh

Arvind Singh

Global Practice Head for Device Engineering

Arvind Singh is a global engineering leader at Quest Global with over two decades of experience guiding safety-critical, compliance-driven products from definition to launch. Combining device engineering depth with expertise in EE & thermal performance, reliability, and lab focused validation, he partners on PRD clarity, turns requirements into verification strategies, and aligns cross-functional teams on outcomes. He’s known for system-level product judgment—balancing performance, risk, schedule, and cost to scale real-world solutions.

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Thomas Winkler

Thomas Winkler

Product & Business Leader, Hi-Tech

Thomas excels at transforming disruptive technologies like XR and AI into high-quality, market-ready products. Drawing on experience from Nokia to startups, he leads offering strategy and builds high-achieving engineering teams at Quest Global. Thomas specializes in human-centered design, ensuring technical solutions meet original intent while delivering the strategic value and usability today’s global markets demand.

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