Structured, low-friction collaboration
We use a simple four-step approach designed to show value quickly, respect your governance, and keep demands on internal teams predictable.
Typical engagements run as short, focused projects with clear milestones and owners.
Our four-step process
Clear stages, defined responsibilities, and a decision point at the end of each engagement.
1. Discovery
Short conversations with key stakeholders to understand the workflow, constraints, and success criteria.
• Clarify objectives and guardrails
• Agree on one or two priority use cases
2. Design & prototype
Translate the workflow into a focused prototype that can be tested quickly with realistic (often de-identified) data.
• Lightweight solution design
• Working prototype around a single use case
3. Feedback & refinement
Work with underwriters, actuaries, operations, and control functions to review performance and fit.
• Capture feedback from end users
• Adjust for risk appetite and governance
4. Decide what to scale
Joint decision on whether to move to implementation, iterate further, or park the idea with documented learnings.
• Plan rollout and monitoring if scaling
• Share a concise summary of outcomes
Who is typically involved
We keep the core group small but representative, so decisions are fast and well-informed.
Business owner
Sets objectives, owns the workflow, and decides how success is measured.
Data / technology lead
Ensures alignment with architecture, data constraints, and security requirements.
End users
Underwriters, analysts, and operations staff who use the tool day-to-day and provide practical feedback.
Control functions (as needed)
Risk, compliance, or model governance teams involved where appropriate for oversight.
Start with a single workflow
Most engagements begin with one clearly defined area where AI could support your teams. From there, we decide together what to scale.
contact@reinsuranceanalytics.io