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Data Migration:
Committed Scope · Predefined Price

A scope defined up front, a price fixed before you are locked in, and a result we prove against the source.

Ofakim Solutions is a data migration company. We move data from legacy and in-house systems into new enterprise platforms (ERP, hospital, financial, operational) and take the whole job: analysing the source data, mapping it to the target with your business users, building and running the migration, and proving the loaded result against the source. The work follows one method. Our Migration Control Center (MCC) is built to carry that method, from the evidence through the mapping and the generated programs to the proof. Our own team does the work, for a price fixed before you commit.

Most migration surprises hide in the data and surface late, when they have the most impact. We work the other way round: an indicative price from numbers you already have (target tables, fields, sources), then a short, fixed-fee discovery that turns it into a fixed price for a defined scope and schedule. We can carry that risk because we trust our methodology, our tools, and our people: the price moves only if the agreed counts change, never because the work ran long. And because a proven method, purpose-built tools, and accelerators do much of the heavy lifting, it is usually lower than what a traditional migration ends up costing.

On this page: how we migrate, one method in five moves; what you gain from it, from early warning of target gaps to a price fixed before you are locked in; the tools that make it possible; where we operate and what we have delivered; and how to start.

How we migrate

One Method, Five Moves

Data leads to rules, rules lead to generated code, and code leads to proof.

  1. Understand the data
  2. Map, business first
  3. Generate the code
  4. Migrate, repeatably
  5. Prove against the source
  1. Understand

    Profile the actual source data: distributions, empty and invalid values, rare codes, relationships. Facts for the mapping sessions, not assumptions.

  2. Map

    Business mapping first: what the target needs, which source information can populate it, what is missing. Technical mapping only once the business decisions are settled.

  3. Generate

    AutoCode turns the approved mapping and rules into the migration programs: extraction, transformation, target files, counters, logging, error handling. What was approved is what runs.

  4. Migrate

    Run the generated programs as a controlled, repeatable process through test cycles, rehearsals, delta runs, and cutover.

  5. Prove

    Compare the loaded target with the source on the items you define: counters, aggregates, or full values. Every discrepancy explained.

The Complete Migration Lifecycle

How we migrate · Why it works

Migration Can Reveal More Than Migration Problems

If it has business meaning, it is in the data.

Working from the actual data, business mapping finds the source-to-target gaps in the first weeks, while they are still design decisions; on a traditional migration they surface in user acceptance testing, months later.

Traditional migration

  1. Build and load
  2. User acceptance. The gap is found months later.

This method

  1. Business mapping. The gap is found in the first weeks.
  2. Then generate, migrate, and prove.
  1. Actual source data
  2. Analysis + business semantics
  3. Planned target model
  4. Business mapping

Every mapped item ends in one of three outcomes

MatchSource meaning is represented in the target. Settled.
Migration gapData or rules that need a decision before load.
Target / functional gapA business scenario the target does not yet address. Raised to the project while it is still a design decision.

And at the end, a successful load is not the evidence: the loaded result is compared with the source, to the depth agreed with you, and every discrepancy is explained rather than lost in load statistics.

The principles behind our work
How we validate and prove

What you gain

What the Method Buys You

The method is not an end in itself. It changes what you get, and when you get it.

Target gaps, months early

Missing functionality and semantic mismatches surface in business mapping, not in user acceptance testing, while they are still design decisions.

No technical rework

Technical mapping starts after the business decisions are settled, and the code is generated from the approved mapping, so nothing is built twice.

A result you can prove

Source-to-target comparison on the data that matters to you, with evidence you can show an auditor, not a load report.

A price fixed before you are locked in

Because effort follows countable units (modules, tables, fields, sources), we can commit early and carry the risk ourselves.

How We Commit Early

We give you a fixed price early, before you are locked in.

  1. Estimate

    An indicative price from numbers you already have: target modules, tables, fields, and source systems. No commitment.

  2. Discover

    A short, fixed-fee discovery on the source files that set the price. You provide those extracts and their layouts. We profile them, confirm the counts, and classify the fields. You keep the scope sheet and the quote either way, and the fee is credited against the project.

  3. Commit

    A fixed scope, price, and schedule. The price changes only if the agreed counts change, at published unit rates. Logic that discovery has set aside as exceptional is outside that price.

What drives the price, and what the scope states

What makes it possible

Migration Control Center (MCC)

MCC connects evidence, mappings, gaps, decisions, generated code, execution, and validation into one governed migration process. Years of migration work, formalised into tools.

Source Analyzer

Profiles the actual source data: content types, value distributions, relationships, representative keys. The evidence for mapping.

Source Analyzer in MCC & Tools

Mapping Workbench

Captures business and technical mapping, rules, counters, gaps, and actions. The single source of truth for code and validation.

Mapping Workbench in MCC & Tools

AutoCode

Generates the migration programs from the approved mapping, so specification, code, execution, and validation stay aligned.

AutoCode in MCC & Tools

Sample Extractor

Identifies record keys and composes representative test samples, so rehearsals and validation run on data that covers the real cases.

Sample Extractor in MCC & Tools

Validator

Completeness counters and record-level checks, source against loaded target.

Validator in MCC & Tools

Orchestrator

End-to-end runbooks: stages, dependencies, retries, full and delta strategies, for predictable cutovers.

Orchestrator in MCC & Tools

Govern

The evidence trail: every decision, session, and change, with who made it and when, linked to rules and results.

Govern in MCC & Tools

Governed AI

AI assists. Decisions remain in human control. It explains analysis results, prepares mapping sessions, and reviews rules. Its output is a recommendation for expert review, and every decision is recorded.

Governed AI in MCC & Tools
Source Analyzer chart for Visit: ward-code distribution, an empty visit-date slice, and a red error bar on status
Source Analyzer on Visit: ward-code distribution, including ??, an empty slice on the visit date, and a red error bar on status.
Explore MCC & Tools

Where we operate

Industries

The method is cross-industry. Our focus is where data complexity, business semantics, and accountability for the result matter most.

Case Studies

Complex Hospital Data Migration

Administrative migration for a major hospital, requiring explicit semantic understanding and migration rules.

Read the case study

Passenger Revenue Accounting System Migration

Passenger revenue, from ticket to settlement, for a major airline, where every amount has to reconcile.

Read the case study

Planning a Complex Data Migration?

Let's examine the source environment, target objectives, and migration challenge.