AI · Cloud · IoT · Integration

AI integration ×
enterprise automation ×
cloud platforms SAINSO TECHNOLOGY · BUILD AI THAT RUNS

AI assistants / RAG knowledge bases Workflow automation IoT platforms AWS / GCP architecture

Sainso Technology delivers AI assistants, enterprise knowledge bases, LINE / ERP / CRM integrations, IoT data platforms, and cloud systems. One engineering team handles discovery, development, deployment, and long-term operations, so AI can move beyond demos and into daily work.

30 minutes · no documents required · reply within 2 business days

40+Projects
12Industries
99.95%Availability
2-4 wksDiscovery
聖索科技
Sainso Technology
SAINSO
AI Systems Integration
+886 976-804-405
info@sainso-tech.com
sainso-tech.com
No. 7, Lane 262, Zhenxing Rd., East Dist., Taichung City 401
Core Services

Five core capabilities
connected into one delivery path

From AI models, system integration, and software engineering to cloud and IoT connectivity, Sainso delivers working systems instead of fragmented vendor handoffs.

01

Artificial Intelligence

AI assistants, RAG knowledge bases, vision, prediction models, and workflow automation.

Best for
Teams with high support volume, complex documents, or repetitive internal workflows
Deliverables
AI chatbot / RAG knowledge base / automated workflows / prediction models
02

System Integration

ERP / CRM / payment / LINE / third-party API integration and data synchronization.

Best for
Companies with multiple systems and disconnected data flows
Deliverables
API gateway / data sync / automation pipeline / monitoring alerts
03

Software Development

Websites, admin panels, SaaS products, mobile apps, and custom enterprise systems.

Best for
Startups, brands, and IT teams that need tailored product development
Deliverables
Web app / admin panel / mobile app / internal SaaS
04

Cloud Services

AWS / GCP architecture, deployment, automation, monitoring, and cost optimization.

Best for
Teams that need scalable infrastructure, reliability, and cost control
Deliverables
Architecture design / IaC / CI/CD / monitoring / cost analysis
05

IoT Applications

Device connectivity, sensors, edge computing, and cloud data platform integration.

Best for
Manufacturing, energy, agriculture, and smart-space operators
Deliverables
Device SDK / edge gateway / time-series data platform / prediction model
In-house Solutions

Reusable AI solutions

We turn repeated industry problems into composable solution modules. Start with one module or plan a complete enterprise AI platform.

01

AI Smart Router

Reduce multi-model API cost and operational complexity

A routing layer for multi-model AI products and internal tools. Centralize model choice, fallback, cost monitoring, and usage controls without locking business logic to one provider.

Infra · LLM Router
View details →
02

DocGen TW

Help sales, legal, and PM teams produce standard documents faster

A document AI workflow designed for Taiwanese legal and business contexts. It combines templates, rule checks, and LLM review to standardize document production.

AI · Document Generation
View details →
03

AI BizHub TW

Bring multiple AI tools into one manageable enterprise platform

A subscription-ready AI tool hub for SMEs and enterprise teams. Combine customer service, documents, reports, marketing, and HR modules as adoption grows.

Enterprise · Digital Transformation
View details →
04

AI Content Publishing SaaS

Reduce the effort behind weekly multi-channel publishing

A content operations platform for marketing teams. It turns ideas, drafts, editing, scheduling, and distribution into a repeatable workflow.

SaaS · Content Automation
View details →
05

AI Influencer Factory

Build a consistent virtual brand character that can operate over time

A toolkit for brands and creators that need consistent AI characters. Define persona, voice, content pillars, scripts, and social assets for long-term operation.

AI · Content Generation
View details →
06

GiftIt TW

Optimize seasonal conversion with a context-aware recommendation engine

An AI recommendation module for e-commerce, member systems, and seasonal campaign pages. Match gift contexts, recipient profiles, and product data to lift conversion.

E-commerce · Recommendation
View details →
Not sure where to start? Let us help you choose →
Case Studies

What AI looks like
in real operations

The following anonymized examples show how Sainso integrates AI and systems across industries. Client names remain confidential under NDA.

38%Downtime reduction
200Machines connected
12 secAverage response time
71%Auto-resolution rate
Manufacturing / Semiconductor
38%↓
Unexpected downtime reduction

Semiconductor plant · Equipment anomaly alerts

Problem200 machines relied on manual checks, with maintenance records spread across systems.
SolutionIntegrated sensor data, maintenance history, and incident logs into an IoT data platform and prediction model.
ResultUnexpected downtime dropped by 38%, with key anomalies flagged roughly 30 minutes earlier.
Outcome-ledIoT Gateway · ML · AWS
Retail / Chain Brand
12sec
Average response time

Retail chain · LINE AI customer service

ProblemPeak wait time reached 6 minutes, and member/order data had to be checked manually.
SolutionBuilt a RAG knowledge base and connected LINE OA, ERP, and customer service workflows.
ResultAverage response time fell to 12 seconds and auto-resolution reached 71%.
Outcome-ledRAG · LINE OA · ERP
Finance / Investment Research
+38%
Strategy hit-rate improvement

Decision assistant · Multi-strategy research platform

ProblemTrading decisions relied on instinct, while backtests, news events, and journals were hard to compare.
SolutionIntegrated market data, strategy signals, LLM summaries, and trade journals into daily decision reports.
ResultStrategy hit rate improved by 38%, with each decision backed by reviewable context.
Outcome-ledLLM · TimescaleDB · Dashboard
Process

Four phases
to make AI operational

Every project moves through measurable phases with deliverables and acceptance criteria, so progress stays visible.

01 · DISCOVER

Discovery

Map processes, data sources, constraints, business goals, and success metrics.

DeliverablesDiscovery report · current-state map · success metrics
02 · DESIGN

Architecture

Plan modules, APIs, data models, cloud architecture, permissions, and delivery scope.

DeliverablesArchitecture document · API spec · fixed quote
03 · BUILD

MVP Build

Validate core logic quickly, then iterate into production-ready workflows and tests.

DeliverablesMVP demo · test report · deployment environment
04 · OPERATE

Operations

Monitor, optimize cost and models, and grow the system as a long-term asset.

DeliverablesOperations plan · monitoring dashboard · monthly optimization report
Sainso Technology
About Sainso

Based in Taichung
building practical systems for real work

Sainso Technology is an engineering team with experience across AI, cloud, backend systems, IoT, and enterprise workflow integration. We believe good technology is proven in systems that actually run.

From the first discovery conversation to long-term operations, the people who build the system stay close to the client.

TaichungDirect engineering team accessAWS / GCP experienceSecurity process aligned with ISO 27001 controlsCustomer data is not used to train models
Team Capabilities

Capability matters
more than placeholder bios

Sainso presents the team through verifiable delivery capabilities: discovery, architecture, development, deployment, and continuous optimization by the same core team.

01

AI application architecture

RAG knowledge bases, multi-model routing, tool calling, evaluation flows, and data security design.

02

Enterprise integration

LINE, ERP, CRM, payments, membership systems, and internal APIs connected into maintainable data flows.

03

Cloud and platform engineering

AWS / GCP, CI/CD, monitoring, permissions, cost optimization, and reliability design.

04

IoT data applications

Device connectivity, edge collection, time-series data platforms, anomaly detection, and dashboards.

Insights

Practical notes
from AI and systems work

Not marketing fluff. These are topics the team has encountered, debated, and refined through projects.

2025 · 04 · 12

RAG vs fine-tuning: which should companies choose?

A practical comparison across cost, maintenance, data security, and update frequency.

AI
2025 · 03 · 30

Three ways to move IoT data from edge to cloud

MQTT, Kafka, or HTTP: which pattern fits your field environment?

IoT
FAQ

Questions we often hear

How is Sainso different from a traditional SI vendor?

Traditional SI work often splits the problem across vendors. Sainso starts with the final operating system in mind and keeps planning, development, AI implementation, and operations within one engineering team.

Can we adopt AI without a mature data system?

Yes. We usually start with 2-4 weeks of discovery to map data sources, process steps, and measurable goals before deciding where AI or automation should enter first.

How is pricing calculated?

We quote by phase and scope rather than open-ended headcount. After discovery, we provide a fixed quote for the agreed build scope.

Will our data be used to train models?

No. Client data is used only for the project, stored according to the client security requirements, and can support private deployment or local LLM options.

Do you provide maintenance after launch?

Yes. Monthly operations and optimization can cover model quality, cloud cost, monitoring, reliability, and workflow improvements.

Contact

Turn what you are considering
into an executable plan

Tell us your industry, current systems, AI needs, and budget range. We will reply within 2 business days and arrange a free 30-minute consultation.

No. 7, Lane 262, Zhenxing Rd., East Dist., Taichung City 401, Taiwan

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