Ragate AX Sprint Program - AI Business Analysis & PoC in 2 Months on AWS

The AX Sprint Program is a 2-month AI adoption engagement by Ragate, structured across 4 two-week sprints. It guides organizations from identifying which business processes to apply AI to, all the way through building a working Proof of Concept — covering the Inventory, Selection, and Validation phases of the AI adoption value chain to accelerate organization-wide AI utilization.

[4-Sprint Structure] Sprint 1 (Day 0–13): Business task inventory — map and document operational tasks across departments; deliver an initial task list. Sprint 2 (Day 14–27): Prioritization and AI governance — evaluate tasks and produce a prioritized task list and a draft AI usage guideline. Sprint 3 (Day 28–41): PoC implementation — build a working Proof of Concept for the selected task. Sprint 4 (Day 42–55): Trial and results review — validate outcomes, produce an ROI estimate, and organize the backlog.

Before the program begins, a 60-minute online Phase 0 concept-sharing session is held to align on challenges and confirm fit. Day 0 features a 2–3 hour in-person joint task inventory workshop. On Day 56, a results presentation shares ROI estimates and task inventory findings with decision-makers.

[6 Deliverables]

1. Task List and Prioritization: A task inventory evaluated across three axes — expected impact, feasibility, and risk.
2. Draft AI Usage Guideline: Developed with reference to NIST AI RMF, ISO/IEC 42001, AI TRiSM, and the AI Business Operator Guidelines 2.0.
3. Working PoC: Standard 1 case (expandable up to 3 cases with paid add-ons; 2 cases may be possible within the base scope for common connector scenarios).
4. ROI Estimate: Quantitative assessment of time savings and monetary value from AI adoption.
5. Backlog: Tasks and challenges not addressed within 2 months, organized with evaluation criteria.
6. Decision Material for Next Steps: Recommended scope, approach, and options for in-house execution or continued engagement with Ragate.

[3-Axis Prioritization Framework] Tasks are evaluated by: Expected Impact (annual time savings = frequency × time per occurrence × number of people), Feasibility (data availability, process documentation, and access permissions), and Risk (data sensitivity and impact of erroneous outputs). Results are classified into four categories: Proceed, Adjust, Hold, or Exclude.

[3 Approaches to Task Inventory] Selected in Phase 0:

• Cross-departmental: Comprehensively map tasks across the entire organization.
• Single department: Deep-dive into one department's tasks to build a focused inventory.
• Pre-selected initiative: Identify high-visibility tasks in advance and tackle them as a priority.

[Challenges Addressed]

• Individual productivity gains are not reflected in organization-wide metrics.
• Inability to decide which business processes to apply AI to.
• Difficulty surfacing a sufficient list of candidate tasks.
• A divide between AI users and non-users, widening adoption gaps across teams and individuals.
• Inability to quantify AI adoption impact, making investment decisions difficult.

[Target Customers and Departments] Suitable for business operations (Sales, Planning, Finance, General Affairs, HR), DX Promotion, IT/Information Systems, Business Units, and Corporate Planning/Management. No restrictions on the number of departments or participant roles.

[AI Execution Infrastructure] Built on AWS using Amazon Bedrock, Bedrock Knowledge Bases, OpenSearch Serverless, Lambda, S3, CloudWatch, and related services.

[Engagement Model] Ragate and the customer collaborate from Phase 0 through Day 56. The customer leads task inventory; Ragate leads PoC development. Support throughout the program includes business-day chat responses and bi-weekly online meetings. Upon sprint completion, customers decide whether to proceed independently or continue with Ragate.