AI Enterprise Landing Strategy
From pain points to landing, from tech selection to optimization. Providing a comprehensive blueprint and decision support for AI transformation.
Enterprise AI Landing Planning
Based on existing pain points, screen high-value, easy-to-land AI scenarios, and output executable roadmaps.
Deep Dive into Pain Points
Interview key staff, identify efficiency bottlenecks and cost issues, output quantified metrics.
Scenario Matching & Screening
Match mature cases with tech directions, use 'Value-Difficulty Matrix' to screen priority scenarios.
Feasibility Analysis
Assess data foundation, IT compatibility, and cost thresholds. Output feasibility conclusions and prerequisites.
Phased Roadmap Planning
Define implementation goals and KPIs, plan scenario blueprints for short-term wins and long-term evolution.
Core Deliverables
Capability & Vendor Selection
Provide decision support for models, products, and vendors around confirmed scenarios to reduce trial-and-error costs.
Requirement Breakdown
- Define core tech specs (precision, speed, deployment)
- Set functional requirements & budget range
- Output selection criteria
Model Selection
- General LLM vs Vertical vs Open Source
- Evaluate adaptability & fine-tuning needs
- Provide model suggestions & cost ref
AI Product Selection
- SaaS Smart Tools vs Platform Products
- Compare functionality, usability & price
- Produce shortlist & comparison table
Vendor & POC
- Recommend capable vendors
- Formulate industry case evaluation list
- Design POC test plan
SEO/AI Search Optimization
Diagnose Generative AI engine performance, output content and tech optimization plans to boost visibility.
Comprehensive Diagnosis
Audit digital asset structure & authority, analyze GenAI engine recommendation priority.
Root Cause Analysis
Locate core issues (unstructured content, lack of authority, poor keyword matching).
Optimization Planning
Formulate AI-friendly content transformation & tech strategies (Schema/Crawler Opt).