Our multimedia design studio · endorphin Creatives 腦內飛制作 ↗
Computer Vision
State-of-the-art CNN and Vision Transformer techniques applied to industrial defect inspection (AOI), security monitoring and medical image analysis.
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NEXT GEN
INTELLIGENCE
We turn data into decisions, and algorithms into competitive advantage.
Neurophin Technology — your strategic core in the age of AI.
- Custom model development
- On-premise / edge deployment
- Security & data protection
- Long-term support
Award
Award of Excellence — 10th Startup Star Competition
SeedSense AI · Smart Seed Screening Platform
Now Enrolling
AI Competency Program — Industry Training｜Smart Logistics Optimization: Delivery Efficiency & Forecasting in Practice
Fully Government-Subsidized
Organizer：Administration of Commerce, Ministry of Economic Affairs Executed by：Neurophin Technology Co., Ltd. Oct 17 (Sat), Oct 18 (Sun), Oct 31 (Sat), Nov 1 (Sun)
About Us
About Neurophin Technology
Business Impact ✕ Research Depth
The brand DNA of Neurophin Technology grows out of a conviction about the nature of intelligence itself.
Our name joins Neuro — the computational architecture of neural networks — with -phin, a suffix drawn from endorphin. It captures what we aim to be: not merely a supplier of algorithms, but an "AI enabling factor" injected into your organization. Like a neurotransmitter unlocking the brain's potential, Neurophin exists to catalyze the digital awakening of industry.
The company was founded by an R&D team trained to the doctoral and master's level, with expertise spanning computer vision, signal processing and deep learning. We focus on the hard engineering problems that off-the-shelf models cannot solve — from visual defect inspection to generative-AI enterprise knowledge bases — and we intend to be the technology partner your digital transformation can rely on.
Neurophin
Technology
AI Development
GPU: 98%
NET: ACTIVE
Our Expertise
Three Core Domains
From sensing to understanding to decision-making — a complete technology chain behind your AI applications.
Generative AI
Enterprise LLM knowledge bases and intelligent assistants. With RAG, AI reads your internal documents — powering automated support and document workflows.
Read MorePredictive Analytics
Extracting value from messy data: demand forecasting models and supply-chain optimization that support precise executive decisions.
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Industries
Industries We Serve
The same core technology takes very different shapes across industries. We know the data characteristics and acceptance criteria of these settings.
Smart Manufacturing
Inline AOI defect inspection, predictive maintenance and yield root-cause analysis, integrated with existing MES/SCADA systems.
Healthcare & Biotech
Quantitative MRI/CT analysis, digital pathology reading assistance and blood-cell classification for clinical and research institutions.
Agriculture & Environment
Pest identification, crop monitoring and environmental image analytics, deployable on drones and fixed cameras at the edge.
Public Safety & Transport
Traffic and crowd analytics, anomaly detection, plate and object tracking — built for low light and cluttered scenes.
Retail & E-commerce
Sales forecasting, inventory and supply-chain optimization, automatic product-image classification and recommendation models.
Enterprise Knowledge
RAG knowledge bases, automatic contract and report summarization, internal AI assistants — documents that finally get used.
How We Work
Six Stages,
Six Stages,
from Idea to Production
The most common reason AI projects fail is not weak models — it is never defining what "success" means. We drive every stage with verifiable milestones, so you always know exactly where the project stands.
Book a Discovery CallDiscovery & Feasibility
Clarify the real pain points, audit available data and hardware, and translate expectations into measurable KPIs. If something is not technically feasible, we say so.
Data Audit & Labeling Strategy
Establish data collection and annotation standards, and introduce semi-automatic labeling to reach sufficient data quality with minimal manual effort.
Proof of Concept
A 2–6 week small-scale validation on your real data, proving technical feasibility and expected benefit — with a full evaluation report.
Model Development & Optimization
Custom architecture design, hyper-parameter tuning, model compression and quantization — balancing accuracy against inference speed.
Integration & Deployment
APIs, on-premise servers or edge devices, integrated with your existing MES, PACS or ERP systems.
Monitoring & Continuous Improvement
Drift monitoring, periodic retraining, support and training — keeping the system effective as your production and business evolve.
Why Neurophin
Why Choose Neurophin
Research-grade depth
Trained at the doctoral and master's level, the team designs algorithms from scratch for problems generic models cannot solve — not just tuning parameters.
End-to-end delivery
Data collection, model training, system integration and front-end — one team, no juggling multiple vendors.
Security & data protection
Fully on-premise and offline edge deployment keeps sensitive data under your control; NDAs and data-processing agreements available, aligned with enterprise security audits.
A long-term partner
Delivery is not the finish line. Monitoring, retraining and training programs help your own team gradually take over.
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Model accuracy
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Successful projects
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Systems in operation
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Custom development
We don't have labeled data. Can we still adopt AI?
Yes. We start by auditing the raw data you already have (photos, reports, sensor logs), then define annotation standards and sampling strategies. Where useful, we introduce semi-automatic labeling — a small amount of manual work combined with model pre-labeling — to dramatically cut upfront cost.
How long does an AI project take?
A proof of concept typically takes 2–6 weeks; full production projects usually run 3–6 months depending on data scale and integration complexity. After discovery we provide clear milestones and a timeline — no open-ended projects.
How is data confidentiality ensured? Can we stay off the cloud?
Yes. We support fully on-premise and offline edge deployment — your data never leaves your network. We can sign NDAs and data-processing agreements before any engagement, and work within your security audit process.
What accuracy can the model reach?
Accuracy depends on data quality, task difficulty and the miss/false-alarm costs you can accept. We do not promise numbers before seeing data; instead, the PoC quantifies metrics on your real data with a verifiable evaluation report.
Do we need to buy GPU servers first?
Not necessarily. Development and training can run on our compute. For production we help you compare on-premise GPUs, edge devices and cloud options by cost and throughput — avoiding unnecessary hardware spend.
Is there support after the project ends?
Yes. We offer drift monitoring, periodic retraining, maintenance and training programs. If you prefer to maintain the system in-house, we also do technology transfer and team training.
Ready to Put AI to Work?
Technical consultation or project collaboration — Neurophin Technology is ready when you are.