AI/DX advisory
Clarify the business problem, usable data, internal owner, risk boundary, and the first practical AI or DX service path.
FortuneTek Continuity / AI-DX Advisory / Grants / Japan-Taiwan Cooperation
FortuneTek service experience, reorganized for practical AI and DX decisions
In-Stars is the public advisory entry point that carries FortuneTek service experience into AI/DX consulting, government grant planning, industry-academia collaboration, Japan-Taiwan cooperation, and practical PoC planning for companies that need a clear next step.
Contact In-Stars for a first advisory discussion
DLINVIDIA DLI instructor profile
NCUNCU business administration teaching profile
DXDX roadmap, ERP/process, AI PoC, knowledge-service preparation
FortuneTek Service Continuity
One public entrance for consulting, project planning, and partner development
Use In-Stars when a company needs a practical first conversation across AI/DX, government grants, industry-academia cooperation, training, Japan-Taiwan business development, or PoC planning.
FortuneTek service continuity
Carry earlier consulting, project, training, and partner-development experience into a single public contact point.
Grant and proposal planning
Review SBIR, SIIR, CITD, AI PoC topic fit, evidence package, proposal story, and review schedule.
Industry-academia collaboration
Connect enterprise topics, research partners, validation fields, delivery roles, and result translation.
DLI / AI training planning
Use hands-on AI learning, industry training, and university teaching experience to align executives and internal teams.
Japan-Taiwan DX cooperation
Support Japan-Taiwan business collaboration, technical proposal translation, market-entry preparation, and partner meetings.
Business Benefits
Concrete business outcomes, not generic AI slogans
The page must answer what a client gets after the first conversation: a prioritized problem map, a feasible PoC scope, decision evidence, and a follow-up path that can become a proposal, grant application, training plan, or implementation project.
Decision clarity in 7-14 days
Turn scattered AI ideas into a ranked use-case map with data availability, owner, risk, and next-step priority.
90-day PoC scope
Define a measurable pilot with problem statement, data boundary, process owner, acceptance metric, and evidence needed for budget approval.
Grant and partner readiness
Translate technical ambition into SBIR/SIIR/CITD-style narrative, industry-academia roles, validation field, and review-ready proof.
Training before tooling
Use DLI and enterprise training readiness to align managers, engineers, and users before buying platforms or AI assistants.
FortuneTek To In-Stars
How FortuneTek content becomes In-Stars conversion content
FortuneTek remains the group trust source. In-Stars turns that source material into focused consulting pages, decision checklists, grant narratives, and delivery frameworks for AI/DX buyers.
From corporate trust to buyer problem
Group history becomes the opening proof, while In-Stars names the concrete AI, DX, grant, PoC, or training problem.
From case story to reusable method
Streetlight, smart care, 3C3I, and collaboration cases become challenge, approach, evidence, and repeatable framework sections.
From inquiry to routed follow-up
Enterprise consulting routes to In-Stars, course/channel/community demand routes to LiUX, and campaign evidence routes through 3JK.
DX Authority Foundation
DX authority foundation: DLI, campus teaching, ERP, and industry-academia PoC
In-Stars presents these public references as role evidence and ecosystem context. They do not imply formal endorsement by NVIDIA, TIBAME, National Central University, UMC, TWAICoE, or any partner organization.
NVIDIA DLI instructor profile
Samuel Liu is positioned through a public NVIDIA DLI Instructor profile as an AI training and hands-on learning reference.
TIBAME NVIDIA DLI instructor
TIBAME course material lists Samuel Liu as instructor for a DLI LLM application course, connecting In-Stars to industry training channels.
National Central University teaching
The NCU Business Administration faculty profile connects AI, LLM/generative AI, AIoT, cloud/edge, agile projects, and enterprise digital transformation.
ERP / process DX
Central University ERP/process teaching context supports process improvement, data governance, and automation planning.
Industry and policy ecosystem
UMC, TWAICoE, and FortuneTek case heritage are described as scenario, policy-resource, and case-asset context, not endorsement.
Consultation Readiness
How In-Stars helps teams evaluate the next move
In-Stars presents advisory work with clear evidence, decision paths, and practical next steps, so enterprise teams can discuss AI, grants, PoC, and collaboration topics with less ambiguity.
Evidence first
Use public experience, training context, and case logic to discuss what can be verified before a project starts.
Decision path
Clarify whether the right next step is consultation, grant preparation, industry-academia matching, or a focused PoC.
Practical preparation
Organize process, data, owner, timeline, and acceptance criteria before tools or vendors are selected.
Clear handoff
Turn the first conversation into a service route, contact window, and preparation list for the next meeting.
Case directions
Turn existing experience into practical business topics
Streetlight innovation to smart-city AI PoC
Turn public-infrastructure innovation into data, operations, and energy-impact validation.
Smart care and learning system field validation
Translate care and learning systems into industry-academia PoC topics.
3C3I to AI marketing automation
Connect customer, content, channel, and insight processes into measurable advisory delivery.
Start with the business decision, then choose the right service path
Share the business topic, current decision, expected timing, and available materials. In-Stars will help decide whether the next step is AI/DX advisory, grant planning, industry-academia collaboration, Japan-Taiwan cooperation, or PoC planning.