LLM-Powered AI Line Bot Development
FlyPig AI builds enterprise Line Bot and AI customer service workflows with LLMs, brand knowledge bases, human handoff and ongoing optimization.
Learn moreEnterprise AI Gateway
Enterprise AI adoption, from workflow to ROI
FlyPig AI helps SMEs organize LLM customer service, Line Bot, ecommerce content, Martech automation and performance tracking into workflows that can be tested, maintained and managed.
FlyPig AI OS
Live workflow24/7AI support
9AI service modules
Knowledge base
Content workflow
Performance tracking
What We Build
Based in Taiwan, FlyPig AI is the AI business unit of iCareU. We combine ecommerce operating experience with LLM, generative image and workflow automation implementation so AI becomes part of daily operations, not only a demo.
Company Background
FlyPig AI grew out of the internal IT and ecommerce operations team of iCareU. The team brings more than ten years of ecommerce, brand distribution and channel operations experience to practical AI adoption projects.
Enterprise AI Solutions
Ecommerce Growth and SEO Planning Tool
A market insight and SEO planning service for ecommerce teams that need faster product positioning, content strategy and conversion-oriented copy.
Learn moreAI Ecommerce Marketing Director
A product content workflow for ecommerce brands: product copy, image direction, SEO content and Meta ad ideas from one structured product context.
Learn moreAI Adoption Process
Workflow audit
Prototype validation
Workflow integration
Launch and optimization
Pricing and Engagement
Workflow audit for opportunity and data readiness
Book a workflow auditPrototype build for one priority use case
Book a workflow auditProduction rollout with governance and maintenance
Book a workflow auditFAQ
Who is FlyPig AI for?
SMEs, ecommerce brands, startups and teams that need to bring customer service, content, marketing or internal workflows into AI-enabled operations.
Can we start with only a Line Bot or FAQ assistant?
Yes. We usually begin with common questions, knowledge sources and human handoff rules, then validate quality in a small workflow.
How long does implementation take?
It depends on data readiness and integrations. A small prototype can be validated in weeks; production rollouts are planned in phases.