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AI TRANSFORMATION CONSULTING

From using AI to becoming AI-native
Multiply organizational capability

Our six-dimension maturity model identifies your current position. Consulting, models and agents support the journey from diagnosis and pilots to organizational redesign.

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WHY TRANSFORMATION

Why has the organization not changed with AI?

Meaningful AI transformation calls for changes in workflows, decisions, structure and culture.

Stuck at individual tools

People use AI, but workflows and decisions remain unchanged. Efficiency gains soon plateau.

Pilots become silos

Early teams move faster while others stall, making lessons difficult to scale.

Plans do not reach practice

The strategy is clear, but product and engineering capacity is missing to put AI into daily workflows.

METHODOLOGY

AI-native organizational maturity model

Four stages and six dimensions show how deeply AI is integrated.

An AI-native organization treats AI as a collaborator embedded in workflows, decisions and value creation, multiplying what the organization can achieve.
  1. 1.0 - 1.5 ptsExploration stageAI has not entered the organization systematically.
  2. 1.5 - 2.5 ptsTool adoption stageAI mainly improves individual productivity.
  3. 2.5 - 3.5 ptsIntegration stageWorkflows and decisions are changing, and AI has entered some key steps.
  4. 3.5 - 4.0 ptsAI NativeAI is deeply embedded in workflows, decisions and value creation, becoming a source of competitive advantage.
D1

When AI gets involved

When does AI enter your work?

  1. Final polish
  2. Occasional support
  3. Early involvement
  4. End-to-end collaboration
D2

Workflow redesign

Would your workflows still work the same way without AI?

  1. No change
  2. Partial integration
  3. Core redesign
  4. AI as infrastructure
D3

Decision-making

Does AI have a role in important decisions?

  1. No AI input
  2. Reference only
  3. Defined decision step
  4. Redesigned authority
D4

Organization and roles

Has AI changed how your organization is designed?

  1. No organizational change
  2. Some roles adjusted
  3. Team collaboration redesigned
  4. System-wide redesign
D5

Culture and values

Is working without AI normal or an exception?

  1. Personal choice
  2. Encouraged, not expected
  3. Team standard
  4. AI by default
D6

Value creation

Does AI change how fast you work or what you can accomplish?

  1. Efficiency gains
  2. Better quality
  3. New capabilities
  4. New competitive position
SERVICES

Five steps from diagnosis to delivery

We set a direction, deliver with product and engineering teams, and review progress quarterly.

  1. 01Self-assessment

    AI-native online assessment

    Free · 5 minutes

    Assess six dimensions and receive your stage, radar chart and priority recommendations.

    • Maturity radar chart
    • Stage assessment
    • Priority recommendations
  2. 02Diagnosis

    Organizational maturity diagnosis

    2–4 weeks

    Interviews, surveys and business data reveal your current stage and key gaps.

    • Six-dimension diagnosis
    • Improvement roadmap
  3. 03Co-creation

    Leadership workshop

    1–2 days

    Align leaders around AI-native work and prioritize high-value pilot opportunities.

    • Opportunity list
    • Pilot priorities
  4. 04Pilot

    Pilot delivery

    1–3 months

    Launch one or two use cases with the LLM MaaS Platform and Agent Framework, then validate results in real work.

    • Working AI use case
    • Outcome evaluation
  5. 05Redesign

    Organizational redesign and quarterly review

    Annual advisory

    Redesign workflows, decisions and roles, then track progress through quarterly reviews.

    • Redesign roadmap
    • Quarterly review report
CASES

Consulting and delivery across five industries

Each case moves from identifying priorities to running AI in real business settings.

Service industryA beauty services chain

Smart store operations

An AI manager supports daily store operations with on-demand data and proactive growth suggestions.

  • D1 AI involvement
  • D3 Decision-making
View case
RetailA retail company

Enterprise Knowledge Agent

Company knowledge becomes a customer-facing agent that is built, validated and improved continuously.

  • D2 Workflow redesign
  • D6 Value creation
View case
E-commerceA cross-border e-commerce seller

Intelligent e-commerce operations

Agents take over repeat tasks so a small team can manage operations from setup to fulfillment.

  • D4 Roles and teams
  • D6 Value creation
View case
InsuranceAn insurance brokerage team

AI-powered insurance sales

AI joins the sales process from needs analysis, freeing advisors to focus on client relationships.

  • D1 AI involvement
  • D4 Roles and teams
View case
Chemical industryA petrochemical laboratory

Intelligent chemical analysis

AI supports the chromatography workflow from peak recognition to conclusions and reports.

  • D2 Workflow redesign
  • D3 Decision-making
View case
AI consulting background

Take the next step in AI transformation

Speak with an advisor about a full maturity diagnosis and improvement roadmap.

Book a consultation