Seize AI Growth Opportunities
We Deliver Results, Not Just Experiments

This rare background means we can approach from a CEO's business perspective, providing both strategically elevated top-level design and hands-on construction of stable, scalable AI engineering solutions. This ensures our solutions not only "sound good" but can "land robustly," truly solving business problems while avoiding the "theoretical empty talk" of pure consulting firms and the "limited perspective" of pure technology companies.

This co-creation workshop is specifically designed for enterprise executives and core execution teams who feel confused about AI transformation direction and haven't unified internal understanding. If your team is struggling with questions like "where to start with AI" and "which scenarios have the highest value," this 4-hour structured workshop can help you quickly build consensus and lock in clear, actionable starting points.

Our core difference lies in "platformization" and "deep business integration." We don't code from scratch but rely on our self-built mature intelligent agent management and scheduling platform to achieve 30-day rapid delivery. More importantly, we deliver not an isolated tool, but a "growth engine" deeply embedded in your core business processes that can continuously iterate, with the ultimate goal of quantifiably improving your business metrics.

We don't provide generic "tool usage encyclopedia" courses. Our training is highly customized, completely centered around the AI platform developed for your enterprise and real business scenarios. The goal is not simply to teach tools, but to cultivate a group of team leaders who can independently use AI to solve practical problems and drive continuous project optimization, truly settling AI capabilities as organizational assets.

Our biggest difference lies in "Business Perspective First". With our founder's 20+ years of combined background in Big Four management consulting and technology practice, we can understand your business challenges from a CEO's perspective, ensuring every AI solution targets measurable business growth as the sole objective.

Absolutely. We don't just deliver tools, but are committed to delivering a team that can effectively use AI. Through courses like "AI Business Transformation Bootcamp", your team will build AI applications hands-on, and we'll truly internalize AI capabilities as your organization's core assets.

We follow a transparent process: 1. Initial Diagnosis (30-min free call) → 2. Strategy Workshop (4 hours) → 3. Agile Delivery (MVA model) → 4. Empowerment & Partnership (long-term).

We uphold the highest standards: supporting private deployment, establishing strict rules against using public AI for sensitive data, and ensuring a "Human-in-the-Loop" for all critical decisions.

We offer flexible pricing models: AI Growth Strategy Co-creation Workshop: Single 4-hour in-depth session; AI Growth Engine Platform Delivery: 30-day MVP delivery model; Customized Enterprise AI Practical Internal Training: Customized based on enterprise scale and requirements. Specific quotes need to be evaluated based on your specific needs.

We provide comprehensive follow-up support: Technical Support: System maintenance, bug fixes, performance optimization; Business Support: Usage training, best practice sharing, business process optimization recommendations; Upgrade Services: Continuous iteration and feature expansion based on business development needs.

The starting point of AI transformation is identifying high-ROI scenarios for priority implementation. A very effective initial goal is: let AI handle repetitive tasks that employees don't want to do. Our "AI Opportunity Four-Quadrant Matrix" tool is specifically designed for systematic evaluation and screening of high-value scenarios.

We provide a clear ROI calculation framework:
ROI = (Employee hourly rate × Time saved - Operating costs) / Development costs
Example: Employee with annual salary of 350K, spending 40 hours monthly on reports, AI agent can save 80% time, annual ROI reaches 9.6.

We recommend starting with business support departments, such as HR, finance, marketing, etc. These departments typically have a lot of repetitive work, where AI effects are obvious and risks are low. Success cases can build confidence and experience for subsequent expansion to core business departments.

The key is to let data speak: 1) Show specific ROI calculations and payback periods; 2) Provide successful cases from the same industry; 3) Start with small-scale pilots and prove value with actual results; 4) Emphasize competitive advantages and market opportunity costs.

Common failure reasons: 1) Lack of clear business objectives; 2) Poor data quality or insufficient data; 3) Organizational change resistance; 4) Disconnect between technology and business; 5) Lack of continuous management support. Our methodology specifically designs preventive measures for these risk points.

We establish a multi-dimensional evaluation system: Financial Metrics: ROI, cost savings, revenue growth; Efficiency Metrics: Processing time, error rate, capacity improvement; User Metrics: Satisfaction, adoption rate, usage frequency; Strategic Metrics: Market competitiveness, innovation capability.

GEO (Generative Engine Optimization) is a strategic process aimed at optimizing brand information to be accurately presented and effectively disseminated in AI-driven generative engines (such as Google's AI Overviews, ChatGPT). Unlike traditional SEO that pursues link clicks, GEO's core goal is to influence AI conversations, allowing brand information to be directly cited, summarized, or recommended by AI. GEO is an evolution of SEO, built on a solid SEO foundation, but with higher requirements for brand authority, conversational content, and multi-platform signals.

Because user information acquisition behavior is undergoing fundamental transformation. Gartner predicts that by 2026, traditional search engine traffic will decline by 25%. Users increasingly prefer to get direct, comprehensive answers from AI rather than a long list of links. Ignoring GEO may mean your brand becomes "invisible" in the future digital world. Early GEO deployment is a key strategy to ensure your brand occupies a leading position in the coming AI search era.

The key first step is to strengthen technical SEO foundations and build your content around E-E-A-T principles (Experience, Expertise, Authoritativeness, Trustworthiness). Generative engines heavily rely on traditional ranking signals to assess the credibility of information sources. Meanwhile, AI models are designed to prioritize content that demonstrates high quality and high credibility. You can find a complete seven-step action plan in our "GEO Implementation Guide."

General AI tools have obvious limitations when handling large-scale or complex data analysis. Main reasons include: 1) Context length limitations, unable to process complete data at once, causing analysis interruption; 2) Lack of business background knowledge, unable to provide truly insightful analysis; 3) Fixed interaction modes, difficult to execute customized analysis tasks requiring multi-step, complex logic; 4) Data security risks, uploading sensitive business data to public platforms poses privacy leakage risks.

Our core difference lies in "customization" and "deep integration." We don't rely on general chat interfaces but build dedicated AI analysis assistants connected to your internal databases. This means: 1) AI can directly access all real-time data for analysis without data volume limitations; 2) We can preset your company's specific business logic, KPIs, and analysis frameworks in the backend, making AI analysis completely aligned with your business objectives; 3) Support automated report generation, AI can produce in-depth analysis reports according to preset templates regularly, greatly freeing up human resources.

The role of human experts is crucial, transforming from "executors" to "strategic guides." AI is a powerful efficiency tool, but the depth and breadth of its analysis completely depend on the frameworks and questions set by human experts. An experienced operations expert can integrate their deep understanding of business into the AI assistant construction process, designing more precise analysis dimensions, thus enabling AI to produce insights with true commercial value that far exceed general tools. Our philosophy is: AI's value depends on human experts' strategic guidance.

We develop based on mainstream open-source technology stack + autonomous construction, ensuring technology foresight and sustainability. Our architecture design has strong modularity and scalability, enabling rapid adaptation to emerging technologies.

Not necessarily. We will first evaluate the effectiveness and limitations of existing tools, then develop the optimal integration plan. Our goal is to maximize the value of existing investments, not to start from scratch.

Data quality is indeed important, but not an absolute barrier. We will: 1) Assess the usability of existing data; 2) Design data cleaning and preprocessing solutions; 3) Start with scenarios that have lower data quality requirements; 4) Gradually improve data quality during AI application process.

We have designed a complete disaster recovery plan: 1) Automatic fault detection and alerting; 2) Automatic backup system switching; 3) Manual takeover mechanism; 4) Quick rollback capability; 5) 24/7 technical support. Ensuring business continuity is not affected.