Objective: Map today’s reality and pinpoint high‑ROI opportunities.

• Stakeholder workshops to surface pain points & goals.

• Rapid data‑quality check - are you AI‑ready?

• Use‑case canvas: rank potential wins by value and feasibility.
  

  You get: Current‑state report, use‑case shortlist, and an executive roadmap.

Objective: Architect the right models, data pipes, and success metrics.

• Define SMART KPIs (MAPE, plan‑adherence, risk‑alert accuracy).

• Draft model & integration architecture (ERP, TMS, WMS hooks).

• Change‑management playbook to drive adoption.
  

  You get: Detailed design doc, tech stack picks, 90‑day build plan.

Objective: Turn blueprints into working solutions.

• Engineer & cleanse data; create feature sets.

• Train/validate forecasting, S&OP, or risk‑alert models.

• Seamless integration with your core systems.
  

  You get: Tested models, sandbox demo, pilot results & user feedback.

Objective: Roll out the solution and upskill your team.

• Phased go‑live with MLOps monitoring.

• Hands‑on training: how to trust and act on AI outputs.

• Hypercare support during the first planning cycle.
  

  You get: Live AI dashboards, trained power users, post‑launch scorecard.

Objective: Keep the models sharp and ROI climbing.

• Track KPIs vs. baseline; publish quarterly value reports.

• Automated retraining to beat data drift.

• Road‑mapping sessions to expand AI into new workflows.
  

  You get: Performance dashboards, improvement backlog, and an embedded path to next‑level gains.