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AI and Automation

Data Migration Automation

Automated data migration for ERP, CRM, and platform transitions.

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Overview

What we deliver

We automate extraction, transformation, validation, and loading of data during ERP, CRM, and platform migrations to reduce risk and cutover time.

We automate data migrations for organizations moving between ERPs, CRMs, HR systems, and other core platforms. Our team builds repeatable pipelines that extract data from source systems, clean and transform it to target schemas, run validation checks, and load through APIs or supported migration tools. We design every migration so it can be run many times in test environments before cutover, with full reconciliation reports comparing source and target. We handle master data, transactional history, attachments, and reference data, working closely with your functional leads to confirm mapping rules. Our automation reduces manual rework, shortens cutover windows, and lowers the risk of go-live data issues. We also help you build a defect log workflow, mock cutover plans, and a final reconciliation pack for audit and sign-off. Where ongoing reverse migrations or system sync are needed, we extend the same pipelines into operational use.

Fit Check

Built for teams like yours

Who it's for

  • Companies running ERP migrations
  • Salesforce or CRM consolidations
  • HRIS and finance platform moves
  • Carve-outs and M and A integrations
  • Data and program management teams

Pain points we solve

  • Manual, error-prone migration work
  • Late discovery of data quality issues
  • Long, risky cutover windows
  • Poor reconciliation evidence
  • Inability to repeat migration test runs
What's included

Capabilities

Everything we cover in this engagement.

  • Source data profiling
  • Mapping and transformation design
  • Automated ETL pipelines
  • Data quality and validation rules
  • Mock cutover runs
  • Reconciliation reporting
  • Defect tracking workflows
  • Cutover and hypercare support
How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Profile

Analyze source data quality and scope migration objects.

02

Map

Define field-level mappings and transformation rules.

03

Build

Develop automated pipelines and validation checks.

04

Rehearse

Run mock cutovers and resolve defects iteratively.

05

Cut over

Execute production migration with reconciliation evidence.

What you get

Deliverables & outcomes

What you get

  • Data profiling report
  • Mapping specifications
  • Automated migration pipelines
  • Validation and reconciliation reports
  • Mock cutover playbook
  • Final cutover evidence pack

Outcomes you can expect

  • Shorter cutover windows
  • Higher post-go-live data accuracy
  • Fewer migration defects
  • Stronger audit and sign-off evidence
  • Reusable pipelines for future moves
Timeline

10 to 20 weeks depending on scope

Engagement

Monthly retainer, Project, Sprint

Tools we use

Talend, Informatica, Azure Data Factory, Python, SQL

KPIs we track

Records migrated, defect rate, reconciliation match rate, cutover duration, mock run count

Client stories

What clients say

"

My books were 90 days behind and I was avoiding my accountant. They cleaned up nine months of mis-categorized Shopify and Stripe entries, set up proper rules in QuickBooks, and now my close lands on day four of every month. First time in three years I opened a P&L without wincing. Cash forecasting actually makes sense now.

D.R.
"

Two weeks before our seed round we still did not have a defensible model. Their fractional CFO rebuilt our three-statement forecast, pressure-tested the assumptions, and walked me through every line before the partner meeting. We closed 1.4M on the terms we wanted. The investor specifically called out how clean the financials looked compared to the last five decks she had seen.

Hannah B.
Proof

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FAQ

Frequently asked questions

Quick answers to the questions we hear most.

Which target platforms do you support?
We work with SAP, Oracle, Salesforce, Workday, Microsoft Dynamics, and most major platforms.
How do you handle data quality issues?
We profile early, define cleansing rules, and report defects so business owners can resolve them in source.
How many mock cutovers do you usually run?
Most programs run three to five mock cutovers before the production cutover.
Can you migrate historical transactions?
Yes, we migrate transactional history when required, balancing scope against cutover time.
Do you provide reconciliation evidence for audit?
Yes, we deliver a final reconciliation pack covering counts, totals, and sample validations.

Planning a major data migration?

We automate migration pipelines so cutover is faster, safer, and audit-ready.

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