Scenario-led deployment built from the existing FDE.HK product system
This page organises the current FDE.HK product catalogue and typical deployment scenarios into a clearer buying path for financial institutions and cross-industry Hong Kong enterprises.
How this page is structured
The solution view is an executive layer on top of the planned FDE.HK catalogue.
Enter by scenario, convert through the existing product system
Choose a financial or enterprise scenario first. The page then maps the need back to FDE.HK products and diagnosis.
Choose the right next step before sharing sensitive information
FDE.HK separates request intake, paid diagnosis, and maturity assessment so enterprise buyers can move from interest to a controlled deployment route.
Submit an enterprise AI request
Best when the team already knows the business scenario, target department, approximate timeline, and product interest.
Submit requestBook a financial AI diagnosis
Best for executive alignment, budget logic, compliance boundaries, and a 90-day roadmap before implementation.
Book diagnosisRun the AI maturity self-test
Best when the organisation is still comparing readiness, data maturity, workflow fit, and first deployment priorities.
Start self-testA simple route helps procurement, business, compliance, and technology teams understand the next decision point.
Give financial buyers a clear reason to trust the next step
FDE.HK is designed for enterprise conversations where procurement, business, technology, and compliance teams all need to understand scope, risk boundaries, and handover before committing.
FDE.HK provides AI deployment and workflow enablement. It does not present unauthorised client logos, licences, partner institutions, or media endorsements, and it does not replace licensed professional judgment.
1 business day intake rhythm
Requests are structured so an advisor can quickly qualify product fit, budget range, timeline, and internal decision needs.
Non-sensitive first, NDA-ready after fit
Buyers can start with business context. Sensitive files should wait until NDA, access rules, and data boundaries are confirmed.
Deployment scope before implementation
Diagnosis clarifies workflow owners, users, documents, integrations, acceptance criteria, and the 90-day route.
Deliverables written for acceptance
Plans, workflow maps, training notes, and acceptance checklists help internal teams move from interest to adoption.
This keeps the conversation commercial, auditable, and useful for internal approvals.
A live-operating website should show how FDE.HK works after the first click
This section turns the business into a visible operating model: request intake, diagnosis, product matching, delivery, acceptance, training, and managed operations. All examples are labelled as demo scenarios and do not imply named clients or endorsements.
Financial AI deployment console demo
A buyer can see how FDE.HK moves from non-sensitive intake to diagnosis, delivery planning, secure handover, and long-term operations.
The console is illustrative. Real projects should use NDA, access rules, approved data scope, and named accountable reviewers before sensitive material is exchanged.
FDE.HK should feel concrete: not a page of slogans, but a service route with tangible documents, controls, and operating assets.
Business context, workflow fit, risk notes, and recommended product route.
What can be submitted, what requires NDA, who can access, and what must be reviewed.
Pilot scope, implementation sequence, training, acceptance, and managed operations.
Launch criteria, reviewer roles, test cases, handover assets, and operating rhythm.
From enquiry to deployment decision
Qualify the buyer, identify first scenario, and avoid asking for sensitive files too early.
From demo to accepted workflow
Turn product interest into permissions, knowledge sources, workflow tests, and team training.
From launch to managed improvement
Keep knowledge bases, AI employee prompts, usage metrics, and SOP updates current.
Start with the planned FDE.HK P0 products
The solution experience keeps the product system intact. Buyers can enter from a scenario, but conversion still maps back to the existing catalogue.
FDE Financial AI Deployment Diagnosis
Assess workflows, scenarios, tool choices, and a 90-day deployment roadmap before adopting AI.
FDE Financial AI Employee
Deploy task-ready AI employees for research, compliance, service, meetings, sales, documents, and IR.
FDE Financial Knowledge Base
Turn reports, product materials, compliance files, SOPs, client Q&A, and historical documents into a permission-aware enterprise knowledge base.
FDE AI Research Assistant
Improve research summaries, issuer data prep, memo drafting, roadshow materials, and research data management.
FDE AI Compliance Assistant
Deploy AI support for compliance documents, internal policy Q&A, process checks, training Q&A, and risk prompts.
FDE KYC / AML AI Support System
Help financial teams organize KYC / AML documents, client data, risk labels, review workflows, and internal records.
FDE Family Office AI System
Deploy private knowledge bases, investment databases, meeting assistants, document management, and dedicated AI assistants for family offices.
FDE RWA AI Deployment Suite
Deploy AI project presentations, document review, investor Q&A, due diligence support, and compliance document assistance for RWA platforms and asset owners.
FDE Secure AI Gateway
Provide a secure deployment layer for AI permissions, model access, data protection, approvals, usage logs, and risk controls.
FDE Financial AI Managed Service
Long-term operations, model tuning, knowledge base updates, workflow changes, training, and monthly reporting for deployed AI systems.
FDE Financial AI Readiness Score
Self-assess AI deployment readiness for financial institutions, with scores, risk notes, and recommended next scenarios.
FDE Financial AI Governance & Policy Pack
Help financial institutions define employee AI rules, data boundaries, approval flows, model usage policies, and internal training materials.
FDE-Finance Financial AI Deployment Certification
Train specialists who can understand financial scenarios, deploy AI tools, build knowledge bases, design agent workflows, and deliver enterprise work.
Use scenarios to explain adoption, not to create new product lines
Before authorised customer cases exist, FDE.HK uses typical deployment scenarios without fabricating client names.
Brokerage AI research assistant scenario
Reports, announcements, financials, and market data are scattered across teams and folders.
Build a searchable research knowledge base and AI summarisation workflow.
Fund AI workbench scenario
Research, portfolio monitoring, and investor communication materials are dispersed.
Create a fund knowledge base, portfolio reporting workflow, and investor Q&A support.
Family office private knowledge base scenario
Investment projects, meeting notes, service records, and family documents need private control.
Deploy a permissioned private knowledge base, project database, and meeting assistant.
RWA investor Q&A scenario
Project materials are non-standard and investor Q&A plus due diligence preparation are costly.
Build an RWA project knowledge base, investor Q&A assistant, and due diligence data room.
Listed company IR AI assistant scenario
Announcements, annual reports, roadshow materials, and investor FAQ need repeated preparation.
Build an IR knowledge base, announcement summaries, and investor FAQ support.
KYC / AML document processing scenario
KYC collection, missing-item alerts, filing, and AML process Q&A consume significant time.
Deploy KYC document structuring, missing-item alerts, and AML workflow Q&A support.
Retail and e-commerce AI service desk scenario
Product data, campaign rules, pre-sales guidance, after-sales policy, and member follow-up are scattered across systems and people.
Build a product knowledge base, pre-sales and after-sales Q&A, and WhatsApp / Website lead reception workflow.
Education and training AI knowledge base scenario
Course content, training materials, learner Q&A, and assignment feedback require repeated organization and updates.
Deploy a course knowledge base, learner Q&A assistant, lesson-plan support, and learning follow-up workflow.
Operations SOP AI assistant scenario
SOP updates are not synchronized, and frontline employees repeatedly ask supervisors about exceptions.
Build an SOP knowledge base, frontline Q&A assistant, quality checklist, and training Q&A workflow.
Manufacturing and supply chain AI assistant scenario
SOPs, quality records, supplier data, quotation files, and maintenance knowledge are scattered and costly to process across languages.
Build SOP Q&A, supplier data, document templates, and quality issue review workflows.
Existing product groups, presented with clearer hierarchy
This grouping is a navigation aid only. It does not replace the product catalogue.
Financial core
Financial expansion
Enterprise and cross-industry AI
Industry vertical deployment
From existing product fit to deployment diagnosis
The workflow follows the original FDE.HK conversion logic: trust, pain, method, product match, risk reduction, and low-friction action.
Identify scenario
Use the typical scenario library to explain the buyer's current problem.
Match product
Map the scenario back to existing FDE.HK products and product pages.
Submit request
Collect non-sensitive company, contact, product interest, budget, and timeline details.
Run diagnosis
Clarify workflow, data boundary, scope, acceptance criteria, and 90-day path.
Deploy and operate
Move into delivery, training, handover, and managed operations where relevant.
Keep the product system intact, then move into diagnosis
If the buyer is unsure which existing FDE.HK product fits, the safest next step is an AI deployment diagnosis.