From Roots to Reach
Reroot
Legacy systems weren’t built to move at today’s speed — and they’re costing you. Missed insights, manual reports, and siloed information keep your team reacting instead of leading. That’s why the first step in any transformation is to reroot your data environment.
Reroot is Vyrdia’s foundational framework for modernizing how your credit union handles information — from ingestion to action. We help you migrate from legacy warehouses, streamline pipelines, and architect for AI, so your data becomes an asset, not an anchor.
John Clapper, Vice President of Engineering
“Before growth comes grounding, a strong ‘root system’ comprised of data. This is how credit unions scale with confidence.”
Reroot
Strengthening your data foundation
Why Reroot?
Every transformation begins beneath the surface. If your data is stuck in legacy environments, fragmented across departments, or missing the agility required to support modern tools — it’s time to reroot.
Vyrdia helps credit unions reclaim control of their data by building secure, scalable foundations. Whether you’re prepping for a core conversion, improving member engagement, or setting up for AI — this is where it starts.
Primary Objectives
Membership Analytics & Enrichment: Identify member trends, opportunities, and gaps in service.
Core Readiness: Clean, well-structured data reduces risk and accelerates timelines for core migrations.
M&A Evaluation: Clean, auditable data increases institutional valuation and simplifies due diligence.
Board Confidence: Consistent metrics drive executive trust and informed strategic decisions.
Who Needs ReRoot?
Credit unions with legacy on-prem data warehouses or fragmented BI tools
Teams preparing for a deconversion or modernization push
CUs exploring AI to drive efficiencey, powering their organization with data
Orgs looking to scale while keeping governance & transparency intact
Leaders seeking immediate clarity from their data assets
Key Roots
Cloud Data Migration: Migrate from on-prem warehouses to the cloud (Snowflake, Redshift, BigQuery, etc.) for scale, security, and savings.
Data Engineering: Design & deploy modern pipelines to streamline ingestion, cleansing, and enrichment.
Business Intelligence & Data Modeling: Migrate, clean, and optimize existing dashboards and data models.
AI-Ready Foundations: Architect environments that support forecasting, personalization, and automation use cases.
