QMY Enterprise Brand AI+

Turning Real Business Problems
intoRunnable Systems

Qu Guangxu · Cross-industry Brand + Business AI Expert · FDE

Cross-domain business flow architect. We don't sell software or push proposals — first, we help you see the problem clearly, then we make the solution work.
Explore
Pain Points

What Business Owners Are Asking

Behind every entrepreneur's confusion lies a real problem worth unpacking

After all these years, the money's coming in — but where do we go next? The old path keeps narrowing, and the new path is still blurry.
How to find your second growth curve?
Has your core competency hit its ceiling? Does what made you win back then still work today? A second curve isn't just 'finding another way to make money' — it's about understanding where you stand on your current curve, how much room is left, and whether you're truly ready for change.
你需要的是
A clear diagnostic of your success path, and a low-cost simulation to validate transformation outcomes before you commit.
Path Dependency DetectionBusiness Simulator
Everyone says enterprise data is valuable — we should invest in data assets. But what's actually worth something, and how?
How to monetize your data assets?
Don't rush to 'monetize' — start with an inventory. What you think is worthless might be gold: customer lists, transaction records, inventory flow data, even return reasons. Only after taking stock can you know what you have, what you can sell, to whom, and at what price.
你需要的是
A diagnostic tool that scans your invisible assets and assigns value, plus a method to cross-analyze that data and find monetization angles.
Data Asset Assessment & ValuationData Mining / Cross-SellingEnterprise Self-Portrait / Asset Blind Spots
We've accumulated years of industry experience, customer data, and internal documentation — can we turn that into a sellable product?
How to commercialize your database / knowledge base?
Three questions must be answered. One: can your expertise run independently without you — is it still accurate? Two: who in the market would pay for it? Three: at what price, and is the math worth it? If you can't answer all three, it's not a product — it's just your personal skill set.
你需要的是
First, diagnose whether your data foundation is 'ready' — structured data can be sold, scattered data can't. Then, help translate industry know-how from 'experience in someone's head' into 'knowledge in a system,' finding a product form that can be priced and sold.
RAG Readiness DiagnosisKnowledge GraphData Mining
I know loyal customers matter — but how much do they actually matter? Which ones could spend more? Which ones are quietly slipping away?
How to increase customer lifetime value through profiling?
You know who's buying. But do you know who's not buying? When did each customer first come? What did they buy? Why did they return — or never come back? If you haven't recorded this, you're always guessing.
你需要的是
A customer profiling engine that reveals who's buying, who's not, and who could buy more — plus an analytics model that uncovers incremental and cross-sell opportunities from your existing customer data.
Customer Profile EngineData Mining / Cross-Selling
We want to expand, maybe franchise — but I'm not confident. Can others really replicate what we've built?
How to scale through asset-light franchising?
The prerequisite for franchising isn't having stores — it's having something that 'others can follow and succeed with.' First, dissect: what in your business can be standardized, and what can't? Why should franchisees trust you — your brand? Your margins? Or just your word?
你需要的是
First, understand your brand DNA — what kind of enterprise you truly are and where your core competitiveness lies. Then check whether the companies you're trying to learn from are even the same 'species' as you. Don't learn from the wrong role models.
Brand DNA DiagnosisTransformation Navigator / Benchmark Detection
We've built this brand for years and spent plenty — but I can't point to what we've actually accumulated. If we changed leadership tomorrow, would any of that accumulation survive?
How to build brand equity that lasts for generations?
Years of brand building — what's actually been accumulated? Brand equity isn't just 'we have a good reputation.' It's: what's worth keeping? How do you keep it? Where do you store it? And once stored, how do you continue using and iterating on it?
你需要的是
First, diagnose your brand DNA — what your core assets truly are. Then manage those assets systematically so they don't depend on any single person — they keep accumulating and appreciating.
Brand DNA DiagnosisBrand Digital Asset Management
Customers aren't where they used to be. How do I make sure they can find me now?
How to reach customers in the digital world?
Your customers are already searching with AI. Are they finding you — or your competitors? What shows up — your decade-old corporate profile, or your latest products? Who ranks higher, and why?
你需要的是
A GEO-building plan that makes AI search engines recognize and recommend you, plus a customer profiling engine that reveals who you're actually attracting — and who you're missing.
GEO (AI Search Visibility)Customer Profile Engine
Every major decision is gut-driven. When it works, I don't know exactly why. Next time, the same uncertainty.
How to improve high-quality decision-making?
Decision-making isn't just the boss's job — it's the company's core asset. When a call works, why did it work? When it fails, why did it fail? Can these be recorded, reviewed, and turned into the basis for the team's next decision?
你需要的是
A low-cost simulation to validate decision scenarios, plus a Judgment Pack tool that captures and preserves the decision-making expertise of both the CEO and key employees.
Business SimulatorJudgment Pack
When people leave, their experience walks out the door. New hires start from scratch. The company's accumulated knowledge lives entirely in people's heads.
How to capture employee expertise as digital assets?
When a key employee leaves, what's lost isn't the client list — it's their judgment: what to do in which situation, and what not to do. Can that judgment stay in the system? Can new hires stand on the shoulders of veterans?
你需要的是
A method to externalize the judgment frameworks of key roles into inheritable digital assets, plus a digital twin system that assists decision-making — so expertise stays with the company, not in someone's head.
Judgment PackFounder Digital Twin
What Next

If These Pain Points Resonate

You'll face three new questions — I'm here to help. Business decision services run through all three lines.

Want AI
But don't know where to start
Enterprise Digital Diagnosis & AI Deployment
We don't sell software or walk in with preconceived solutions. First, we see the bottlenecks in your business, then determine where technology can intervene — ensuring precise investment.
Want a Brand
But you've done so much and still can't say who you are
Brand Strategy & Founder IP Development
From brand audit, positioning, and architecture to founder IP system building. Brand should be leverage — turning momentum into leasing power, government partnerships, and customer trust.
Want Change
But organizational inertia is too strong
Organizational Change & Hands-On Execution
We don't hand over a report and walk away — we execute alongside your team. New teams, new structures, new rules — all advancing in parallel until plans become real change.
Qu Guangxu's Judgments

Independent Judgments

Not predictions — observations repeatedly validated on the front lines as an FDE

In an age of cheap answers, the depth of your questions — your ability to precisely define problems — determines the boundaries of your business strategy.
AI can answer any question, but it can't ask the right question for you. The person who asks the right question is the稀缺 one.
Model capability does not equal business value. A powerful model that isn't embedded in your business workflow is just a demo. Human-AI collaboration is the real key to deployment.
Buying AI isn't the destination. Putting AI into real business processes and getting real results — that's the destination.
The core of AI-native engineering isn't stacking tools — it's reshaping the organizational skeleton.
Most companies are just putting AI wallpaper on old houses — installing Copilot, connecting an API — without touching the underlying structures: workflow, review mechanisms, quality gates. 90% of enterprises get stuck at the diagnosis stage.
A company's most valuable asset isn't the records in its database — it's the judgment frameworks decision-makers use in critical situations. The problem: judgment walks out the door with people.
When a key employee leaves, what's truly lost isn't client lists or process docs — it's the decision intuition accumulated around 'what to do in which situation.' Keeping judgment in the system is the most underestimated proposition in enterprise digitalization.
AI is driving the barrier to execution toward zero — which makes 'knowing what to execute' the only remaining moat.
When everyone can deploy AI to get tasks done, differentiation no longer comes from who can do it — it comes from who defines what to do. The moat isn't access to tools; it's judgment: knowing, in a given business context, which direction to point AI.
Qu Guangxu's Methodology

AI Neural Hub

Technical concepts explained in language business owners understand — because understanding precedes decision-making

OntologyKnowledge GraphOAGSemantic LayerDigital TwinAgent Data FoundationRAGAgentic RAGAI-Native EngineeringFDEData GovernanceEnterprise Semantic LayerJudgment PackKnowledge Middle PlatformMemory GraphVector SearchFull-Text SearchGraph Query
Semantic Layer
Getting the whole company to agree on what the same word means. Does Finance's 'wastage' mean the same thing as Operations' 'cost'? Each department keeps using its own language, but at the data level, the semantic layer lets AI know — they're talking about the same thing.
Knowledge Graph
Weaving the knowledge scattered across departments, systems, and veteran employees' minds into a single network. It's not about storing documents — it's about storing relationships and logic. Searchable, reusable, and the knowledge stays even when people leave.
Digital Twin
A digital mirror of your enterprise. Before making a decision, simulate it in the mirror first — what happens if we expand capacity? Adjust pricing? Switch suppliers? Simulate first, then act.
OAG — Ontology-Augmented Generation
A step beyond RAG. RAG is 'search documents, then answer.' OAG is 'understand your business logic, then answer.' It knows your company's 'procurement' works differently from others — because it first built your enterprise ontology.
Agent Data Foundation
Letting AI safely access your data. What needs to be queried can be queried; what shouldn't be seen stays invisible. Permissions, lineage, audit trails — all managed within the foundation. This isn't handing AI the keys to your database.
AI-Native Engineering
It's not about buying tools and calling it 'AI transformation.' It's a full restructuring: workflow, review mechanisms, quality gates, and accountability. Observation from Limestone Digital: 90% of enterprises stall at the diagnosis stage — unwilling to touch their own bones.
On-Premise Deployment & Data Sovereignty
If your data can't leave the company premises — compliance requirements, trade secrets, customer privacy — it's entirely technically feasible. AI models deployed locally, data stays within your intranet, all computation runs on your own servers. Powerful AI doesn't require the cloud — private deployment gives you full control over your data.
Ontology — AI + Enterprise Ontology + MCP
Your enterprise already has ERP, CRM, OA… tearing everything down isn't realistic. MCP (Model Context Protocol) lets AI securely 'plug into' all your existing systems — not replace, but connect. First, establish your enterprise ontology (unified business semantics). Then, through MCP, let AI call upon the data and capabilities of each system. Legacy systems keep running; AI becomes their unified interface.
Judgment Pack
Every person in a key role has a mental framework for 'what to do in which situation.' A Judgment Pack externalizes that tacit judgment — deconstructing a veteran's decision logic, structuring it, and storing it in the system. People may leave, but the judgment framework stays. New hires start standing on the shoulders of veterans, not from zero.
Process & Products

From Diagnosis to Partnership — Every Step with Tool Support

We don't sell software — we match the right diagnostics and tools to your stage

1

On-Site Diagnosis

1-2 weeks. It's not what you say the problem is — it's what I see. First, understand brand DNA, data readiness, change readiness. Prescribing without diagnosis is the biggest waste.

2

Solution Design

Based on diagnosis, design an actionable path. Clarify the 'why' and 'how to measure' every step. Two parallel tracks: the pain-point track launches immediately, the foundation track advances in parallel — address symptoms and root causes together.

3

Hands-On Execution

We don't hand over a report and walk away. We execute alongside your team — turning plans into real change. Digital twin / Agent support + GEO building run in parallel.

4

Measured Tracking

Build a measurement system. Data-driven continuous optimization — keep going where it works, adjust where it doesn't. This isn't a one-time project; it's establishing a continuously running mechanism.

Foundation Layer · Diagnostics

Two gates every enterprise must pass before AI deployment
Brand DNA Diagnostic
See clearly who your enterprise is
解决:Brand positioning disconnected from actual operations
交付:Brand DNA report + Core asset map
Path Dependency & Change Readiness Check
Has your core strength become your ceiling?
解决:No clear direction for the next move
交付:Path dependency diagnosis + Change readiness assessment

Entry Layer · Pain-Point Driven

Start with the most urgent problem — data starts running immediately
RAG Readiness Diagnosis
AI can't help you because your data isn't ready
解决:Scattered, unsearchable data
交付:Data readiness report + Governance plan
Customer Profile Engine
Know who's buying — and who's not
解决:No full picture of your customers
交付:Customer profile model + Lifecycle analysis
Intelligent Inventory Tracing
Where your goods go, crystal clear
解决:Opaque inventory flows
交付:Flow tracker + SKU tracing system
Data Mining & Cross-Selling
Three years of POS data, finally put to work
解决:Data exists but isn't monetized
交付:Cross-analysis model + Incremental recommendation engine
CEO AI Coach & Decision Agent
High-quality business decisions, no longer resting on one person's gut
解决:Decisions lack data support; experience can't be captured
交付:Decision Agent + Executive dashboard + Judgment Pack system
Founder IP & Digital Twin
When key people leave, their judgment stays
解决:Founder IP can't be replicated; experience walks out the door
交付:Brand knowledge graph + Digital twin + IP content system
Enterprise Knowledge Base Commercialization
Turn industry know-how from head knowledge into sellable products
解决:Tacit expertise can't be standardized or priced
交付:Knowledge base setup + Knowledge graph + Commercialization roadmap

Deepening Layer · On-Demand

Targeted deepening after diagnosis
Enterprise Self-Portrait / Asset Blind Spots
What you think is worthless might be gold
解决:Unaware of hidden assets
交付:Asset blind spot scan + Valuation reference
Business Simulator
Simulate before you decide
解决:No confidence in major decisions
交付:Sandbox simulation engine + Multi-scenario modeling
Transformation Navigator / Benchmark Detection
Is who you're learning from even the same species?
解决:Learning from benchmarks didn't work
交付:Benchmark database + Transferable element extraction
Data Asset Assessment & Valuation
What's your data worth — and who decides?
解决:Have data but don't know how to monetize or price it
交付:Data asset inventory + Valuation assessment + Commercialization path
Services

Four Capabilities, One System

Each line operates independently, but they reinforce each other logically

Enterprise AI
Deployment System
Data Governance
& Knowledge Infrastructure
Foundation
AI Agent
& Development
Execution
Brand Diagnosis
& Digital Assets
Strategy
Decision Tools
& Business Simulation
Decision
Govern data first
Then build Agents
Diagnosis guides governance
Simulation validates Agents
Deployment

Industries × Solutions

Cross-industry pattern recognition — reusable judgment frameworks for every sector

Chain RestaurantsConsumer GoodsBrand GlobalizationRetail ChannelsBrand RejuvenationAI CreativeTalent IntelligenceAI TransformationContent GlobalizationInsurance

Chain Restaurant AI Operations Brain

From single-store model to multi-store coordination — AI monitors per-store labor efficiency, space productivity, and product performance in real time. Anomalies trigger automatic alerts. Business decisions shift from 'the boss's gut' to 'data pushing you forward.'
Business SimulatorData Mining / Cross-SellingIntelligent Inventory Tracing

Consumer Goods AI New Product Launch Engine

New product launches no longer rely on gambling. From consumer insights and concept testing to launch tracking — AI assists decision-making across the full chain: which concepts deserve investment, which channels to hit first, how to set pricing.
Brand DNA DiagnosisCustomer Profile EngineBusiness Simulator

Brand Globalization AI Full Chain

Going global isn't translating your website. From overseas consumer perception and localized content strategy to AI search visibility — we build your digital presence so international users can find you, understand you, and trust you.
GEO / Content DistributionAsset Blind Spot ScanTransformation Navigator / Benchmark Detection

Retail / Channel AI Sales Enablement

Sales associates aren't just 'selling products' — they're understanding customers. AI equips store staff with real-time customer profiles, recommended talking points, and cross-sell opportunities — making every storefront perform like your top salesperson is running it.
Customer Profile EngineData Mining / Cross-SellingKnowledge Graph

Brand Rejuvenation / Narrative Reinvention

A legacy brand isn't 'outdated' — its story just hasn't been heard by today's audience. From brand DNA analysis to contemporary language translation, we reactivate brand equity within a new narrative framework.
Brand DNA DiagnosisPath Dependency DetectionEnterprise Self-Portrait

AI Creative Localization Pipeline

Creative production isn't 'coming up with ideas' — it's building a pipeline. From local cultural insights, creative generation, and multi-variant testing to distribution tracking — AI transforms creativity from an artisan workshop into a reusable industrial pipeline.
GEO / Content DistributionCustomer Profile EngineBrand DNA Diagnosis

Large Organization Talent Intelligence Matching

The biggest cost in large enterprises isn't salary — it's 'people in the wrong seats.' AI Agents build talent profiles, capability maps, and role matching for organizations — not replacing HR, but freeing HR to do 'human work.'
Knowledge GraphEnterprise Self-PortraitJudgment Pack

Traditional Brand AI Transformation Consulting

Traditional enterprises don't lack industry depth — they lack the ability to translate that depth into a language AI can understand. From data readiness diagnosis to AI deployment roadmap, we help legacy brands reclaim their initiative in the AI era.
RAG Readiness DiagnosisPath Dependency DetectionTransformation Navigator / Benchmark Detection

AI Short-Form Video / Content Globalization

Content globalization isn't translating subtitles. From localized narrative reconstruction and AI-assisted production to cross-platform distribution — we make content come alive in different cultures, not just get translated into them.
GEO / Content DistributionBrand DNA DiagnosisDigital Twin

Insurance Industry · Personal IP Mini-Program Solution

A rapid site-building solution for insurance professionals — create personal mini-programs, mine practitioners' tacit judgment experience through Q&A, and transform it into shareable personal judgment packs. Turn every client consultation into a showcase of your professional expertise.
Q&A Knowledge MiningJudgment PackRapid Mini-Program Builder
Thinking

Articles

Ongoing writing on enterprise AI deployment, brand strategy, and business judgment

Loading...
View all articles →
About Me

Personal Analysis

Qu Guangxu
Cross-Industry Business Anatomist
17 years across industries. Brand strategy, front-line operations, technical systems — done all three. I don't stand inside any single discipline to look at problems — I stand in front of the real business, take the problem apart, and make the solution work.
CEO CoachingFounder IP Digital TwinExecutive Management ToolsFDEProduct DiscoveryEnterprise Digital Asset Building & Management
Who I Am
Enterprise AI deployment strategist & executor
Someone who turns real business problems into runnable systems
My Perspective
Cross-domain business flow architect with a holistic view
Moving beyond traditional expertise — are you looking for yesterday's specialist, or building tomorrow's cross-disciplinary generalist?
What I Do
Empower CEOs with high-quality business decisions, mine enterprise know-how, and create second growth curves
Architect AI business scenarios on top of your operational structure
Sales leads, building hit products
Know AI's boundaries, business scenarios, and AI application commercialization

FDE Is Not a One-Person Superhero

FDE (Frontier Deployment Engineer) is an Echo + Delta two-person collaboration model — not one person doing everything. Echo (Qu Guangxu): cross-industry business expert, skilled at identifying and deconstructing problems, translating vague business confusion into actionable technical propositions. Delta (Implementation Expert): prototype engineer, rapidly turning solutions into runnable systems.
🔍
Echo · Qu Guangxu
Cross-industry Business Expert
Find the problem · Deconstruct it
Translate vague confusion into technical propositions
+
⚙️
Delta · Implementation Expert
Prototype Engineer
Rapidly turn solutions into runnable systems
There's a misleading narrative in the market right now — hiring FDEs against a 'superhuman全能' standard. You either can't find anyone, or the person you find is weak in at least one of the two: business understanding or technical translation. Our approach: two people, one collaboration protocol, one delivery result.
17 years across 5 industries. From international 4A agencies serving Coca-Cola, Dior, and Armani, to creating the Panlong·Lotus Place brand for commercial real estate, to dual-brand management for a SaaS product, to digital retail transformation for tea enterprises. Has walked the full chain: brand 0→1, 1→IPO, single brand → brand architecture. PMP certified, 6+ years of VP/GM-level management experience.

Case Highlights

Tea Retail Enterprise · Full-Chain Digital Transformation
Diagnosis revealed brand positioning disconnected from profit structure — 'wholesale DNA wearing a brand skin.' Brand strategy overhaul + digital marketing → private domain ops → store digitalization full chain + product traceability + SEO. Online sales up 30%, customer acquisition cost down 15%-35%.
Commercial Real Estate Group · Brand Creation & Asset-Light Expansion
Full-scope brand 0→1: positioning, naming, commercial planning, asset-light operating model. Turned brand momentum into leasing power — introduced multiple Fujian first stores (Michelin/Golden Phoenix dining, international hotel brands), building a replicable model for asset-light output. Simultaneously audited the shopping center's VIP database, discovered high-net-worth customer consumption blind spots, and transformed findings into an annual VIP event series — resulting in significant increase in VIP engagement and average transaction value.
SaaS Tech Company · Dual-Product Brand Management + Government Partnership
Simultaneously managed B2B teacher-side and B2C parent-side brands (millions of active users), driving BI systems and data-driven decision-making. Brand narrative translated into government collaboration — Phase 1 government funding of 50M RMB, Phase 2追加 70M RMB.
IT Supply Chain Enterprise · Replacing Price Wars with Brand Capability
Advanced from tier-3 to tier-2 supplier — no longer competing on price alone. Systematic brand proposal capability building + retail dealer CRM built from 0→1. Professional expertise replaced price competition.
Beauty Industry Chain · Brand Alliance Strategy
Brand DNA identification and alliance strategy analysis. Diagnosis revealed that the single-store customer-relationship DNA couldn't support chain expansion — the founder's personal IP was both the core asset and the ceiling for scaling. Proposed a brand alliance model instead of direct expansion, saving the founding team over 10 million RMB in avoided losses.
Fortune 500 IT Enterprise · Offline Roadshow Monetization
Designed customized pitch solutions for nationwide offline roadshows, translating product and technical information from the corporate knowledge base into commercially viable industry solutions. Simultaneously built a CRM system with a user points and loyalty program, achieving a doubling of VIP customer engagement and on-site roadshow conversion rates.

Leave your question and contact info — let's talk

We don't sell software, we don't push proposals — let's first talk about what your business is facing, and see if I can help
曲小楼
Questions? Ask me
曲小楼
Qu Xiaolou
Qu Guangxu's Digital Twin
I'm Qu Xiaolou, Qu Guangxu's digital twin. If you have questions about your business, feel free to ask me first.

Message Qu Guangxu

Message Sent

Qu Xiaolou has received your message.
Qu Guangxu will contact you via WeCom shortly.