Our Engagements

A structured path from strategic clarity to measurable operating results.

Every engagement begins with the same conviction: AI doesn't fail because the tools don't work. It fails because there is no operating model change. Our engagement model meets you where you are — from building your first coherent AI strategy to transforming how your organization operates at the executive level.

CEO / COO

Questionnaire

Goal: identify where speed is lagging, where AI creates compounding advantage, and force near-term decisions.

Which engagement is right for me?

Answer two quick questions to find the right fit.

Select an option on the left to see the recommended engagement tailored to your situation.

Trusted by Revenue Leaders

"Working with RMG Associates fundamentally changed how we approached product development. They helped us align the leadership team around a sharper value proposition and a disciplined execution model. The result was faster time to market, clearer accountability, and a measurable reduction in operating expense. This wasn't incremental improvement — it was structural acceleration."

OwnerInsite

Steve Harper

CEO, OwnerInsite

Additional Services

Beyond the core engagement model, we offer targeted advisory for specific needs.

Snowflake AI Data Foundation-in-a-Box

Productized "get your data into shape for AI" for Snowflake‑centric shops.

Typical Scope

  • Standardized ingestion patterns (e.g., CRM/ERP/support tools) into Snowflake, plus basic modeling for 3–5 core domains (customers, products, tickets, usage).
  • Implement or extend a medallion‑style or dimensional model suitable for analytics and feature generation.
  • Baseline governance: roles, warehouses, cost controls, and tagging for AI workloads.

Standard Deliverables

  • Reference schema + dbt or SQL templates.
  • "AI‑ready" views/tables (unified interaction history, customer 360 slices) all later projects can rely on.
  • Runbook for ops and monitoring (job health, cost, data quality checks).

Databricks Lakehouse for AI Workloads

Targeted setup for ML/GenAI experimentation.

Typical Scope

  • Standardized lakehouse setup: Unity Catalog, Delta tables, dev/test/prod workspaces.
  • Ingestion patterns from data warehouse, SaaS tools, and event streams into a curated Delta layer.
  • Boilerplate notebooks or repos for common AI workloads (RAG, churn models, anomaly detection) with MLflow tracking.

Standard Deliverables

  • Lakehouse architecture diagram and config baseline.
  • Template projects (e.g., "Customer Risk Scoring," "Support Ticket Triage") lightly customizable per client.
  • Governance + MLOps checklist (approvals, deployment patterns, monitoring metrics).

Codebase & Systems Audit

Deep assessment of your technical infrastructure, processes, and workforce against your AI strategy. Identifies the gaps between your current state and your target operating model.

AI-Enabled Product Design

If your strategic position is LEAD, we help you design and build the AI-native capabilities that differentiate you in the market.

Executive FAQ

What an engagement is—and is not.

What should we expect from an AI strategy engagement?

Expect a leadership-first arc: align on objectives and decision owners, assess readiness across data, platforms, and workflows, interview key stakeholders, then prioritize opportunities and convert them into a sequenced roadmap. Deliverables typically include a board-ready summary, internal communications guidance, and a 90-day plan with ownership and metrics—not a slide deck that sits on a shelf. Pilot programs add a weekly executive steering cadence and production-oriented workflows with tracking against defined ROI.

The first step is a conversation, not a commitment.

Start with a confidential discovery call. We'll discuss your current position, where the highest leverage is, and which engagement makes sense for your organization.

Assess Your AI Operating Maturity