Built by senior data architects, not coding copilots
BEFORE
18weeks
NOW
8days

Cut data modernization discovery from months
to 8 days.

AI-augmented assessment, architecture planning, fact-based estimation, reverse engineering, and bulk code conversion. For migration or greenfield modernization to Microsoft Fabric, Snowflake, Databricks, BigQuery, and Redshift.

See the 8-Day Modernization Canvas

Fixed scope. Fixed price. Director-level signing authority.

THE DELIVERABLE
The deliverable
Modernization Canvas
Delivered in 8 days
MigrationGreenfieldSource-connectedArchitect-grade
01
Estate inventory
Migration
1,247 objects discovered from live system
01
Data feeds + KPIs
Greenfield
12 data feeds, 28 KPIs, business objectives mapped
02
Granular complexity scoring
847 low312 medium88 high
03
Architecture plan
Lakehouse + medallion, 4 workspaces
04
Roadmap + plan
Detailed WBS, effort estimation, wave plan
05
Target models + code
Target data models, auto-generated ETL, bulk converts
Reviewed by senior architects. 25 years enterprise data DNA.
FROM
Synapse Dedicated PoolSSISTeradataOracleSQL ServerNetezzaDB2HadoopGreenfield inputs (feeds, KPIs)
TO
Microsoft FabricSnowflakeDatabricksBigQueryRedshift
8 days
SQL Server -> Redshift modernization for a Brazilian SI. $150K saved on discovery.
1,600 tables
Catalogued in 3 days post-acquisition for an Australian retailer modernizing on BigQuery.
8 weeks
Databricks -> Fabric modernization for a global manufacturer. Zero business disruption.

How the Modernization Canvas gets built.

DAYS 1 -> 2

Assess

FOR MIGRATION
Source-connected estate inventory, metadata extraction, dependency mapping
FOR GREENFIELD
Data feed analysis, KPI capture, business objective mapping
WHAT YOU GET
A full inventory of your data estate: live object counts, dependencies, and metadata. Or a clean greenfield input map.
Reverse EngineerMetadata IntelligenceForward Engineer
DAYS 3 -> 6

Plan

  • Granular complexity scoring (1 -> 5 per object)
  • Target architecture design (Lakehouse, medallion, workspaces)
  • Detailed WBS, effort estimation, skills matrix
  • Wave plan + risk register
WHAT YOU GET
A complexity-scored, architecture-grounded plan with effort estimates director-grade enough to sign off on.
Forward EngineerMigrateTo Fabric
DAYS 7 -> 8

Convert + handover

  • Target data models + DDL
  • Auto-generated ETL pipelines
  • Bulk-converted sample code
  • Synthetic samples for safe validation
  • Canvas handover + knowledge transfer
WHAT GETS HANDED OVER
Working code, synthetic data for validation, and a Canvas your team owns and runs after we hand it over.
Code ConversionMigrateTo FabricSynthetic Data

How Do We Help?

Agentic AI accelerators infused with specialized data engineering expertise, behaving like niche-skilled engineers. Deploy in weeks, reuse forever.

Before
Manual SQL and ETL conversion across platforms
After
3X to 5X faster code conversion across platforms
Before
Limited expertise in solutioning, data modeling, and code generation
After
Solutioning, data modeling, and code generation in days
Before
Slow reverse engineering of complex legacy systems
After
Legacy system discovery in hours, not months
Before
Weak program planning and effort estimation
After
SI-grade strategy, roadmaps, and estimates in hours
Before
Missing metadata, documentation, and SME context
After
Metadata, lineage, and documentation auto-generated
Before
Testing and deployment not aligned to migration complexity
After
Testing and deployment tailored to actual scope
Before
Limited ability to identify AI acceleration opportunities
After
Teams enabled to apply AI across the lifecycle

Our Offerings

From pre-built accelerators to full-stack data engineering delivery, we help enterprises build, modernize, migrate, and scale data platforms faster.

Data Engineering Accelerators

Pre-built, enterprise-grade data engineering accelerators you can deploy in weeks

Learn more

AI Augmented Full Stack Data Engineering

We design, build, migrate, and operate modern enterprise data platforms using senior engineering expertise and AI-augmented accelerators.

ARCHITECTUREDATA MODELSPIPELINESAI & ANALYTICSTESTINGGOVERNANCEFULL STACK DATA ENGINEERING
Learn more

Who We Work With

We partner with enterprise teams planning, building, and modernizing data platforms.

Data Engineering Leaders

For leaders driving strategy, modernization roadmaps, platform decisions, and delivery planning.

Faster PlanningBetter EstimatesClear RoadmapsCost OptimizationAccelerated Delivery

Data Engineering Teams

For teams building greenfield platforms, data models, pipelines, validation frameworks, and AI-ready data foundations.

Architecture BlueprintsETL Code GenerationFaster Data ModelingBulk Code ConversionAutomated Validation

System Integrators

For SI teams delivering complex migration, modernization, and client transformation programs.

Faster ProposalsBetter EstimatesAccelerated ModernizationMigration AccelerationDelivery Confidence

Our Accelerators are Unique

Built by data engineers, for data engineers. Infused with 25+ years of distinguished-grade expertise and Fortune 50 experience.

Purpose-Built for Data Engineering Use Cases

Agentic Intelligence, Not Just Automation

Reusable, Configurable, and Enterprise-Ready

Infused With Distinguished-Grade Data Expertise

Purpose-built for real data engineering work

Built ground up for core data engineering functions, including niche skills like architecture, planning, estimation, ETL code generation, code conversion, validation, and proposals.

Infused with senior engineering expertise

Embedded with 25+ years of seasoned data engineering skills as knowledge bases, decision logic, workflows, templates, and validation rules.

Agentic intelligence, not simple automation

Our accelerators reason through complexity, understand dependencies, handle edge cases, and generate outputs like senior data engineers.

Reusable, configurable, and enterprise-ready

Designed for repeated use across projects, platforms, and teams with SI-grade deliverables, governance-ready documentation, and quality controls.

Learn How We're Different

Our Flexible Delivery Models

Choose the engagement model that best fits your needs and goals

Accelerator Ownership & Enablement

  • Deploy accelerators directly in your secure environment
  • Comprehensive training to empower your team independently
  • Optional full source code ownership for complete control

Co-Delivery Partnership & Support

  • Jointly deliver outcomes on real production programs
  • Expert-led setup, execution, and continuous optimization
  • Ongoing support, guidance, and knowledge transfer included

The Outcome

Measurable impact on your data engineering initiatives

0%

Faster Delivery

Deliver in weeks instead of months

Up to 40% Faster

0%

Lower Costs

Right-sized teams, automation at scale

Up to 60% Less Manual Effort

0%

Higher Quality

SI-grade, standards-compliant outputs

95%+ Accuracy

Frequently Asked Questions

Answering common questions about 3X Data Engineering to help you get started on your modernization journey.

The Modernization Canvas is the deliverable from a 3XDE Modernization Assessment, produced in 8 business days. It includes source-connected estate inventory, granular complexity scoring per object, target architecture for Microsoft Fabric, Snowflake, Databricks, BigQuery, or Redshift, a detailed roadmap with work breakdown structure and effort estimates, and target data models with auto-generated ETL and bulk-converted sample code. Every Canvas is reviewed by a senior architect before delivery.
AI-augmented data engineering is built for enterprise data engineering leaders, data platform teams, enterprise architects, modernization program leaders, migration leaders, and technology executives managing large-scale data programs. It is especially useful for teams running migrations, greenfield builds, legacy ETL modernization, or stalled discovery phases where source systems are undocumented and the SMEs are no longer available.
AI-augmented data engineering uses purpose-built AI accelerators, metadata intelligence, and codified engineering patterns to compress repetitive work across the data engineering lifecycle. It applies to discovery, complexity scoring, architecture design, data modeling, code conversion, testing, validation, and documentation. Engineers stay in the loop on architecture decisions and edge cases. The accelerators handle the volume work.
Best-fit projects include enterprise cloud migration to Microsoft Fabric, Snowflake, Databricks, BigQuery, or Redshift; greenfield platform builds; legacy ETL modernization including SSIS, BTEQ, and PL/SQL conversion; reverse engineering of undocumented stored procedures; metadata discovery on post-acquisition estates; and migration assessments where teams need a fact-based plan before scoping execution. Engagements run from 5 business days to 24 weeks depending on scope.
Source platforms supported include Synapse Dedicated SQL Pool, on-prem SQL Server, Teradata, Oracle, SSIS, Netezza, IBM DB2, MySQL, PostgreSQL, and Hadoop. Target platforms include Microsoft Fabric, Snowflake, Databricks, Google BigQuery, and AWS Redshift. Greenfield modernization projects with no legacy source are also supported, with input data feeds and KPIs replacing source-system discovery.

Let's talk scale.

Our team of engineering experts and AI architects is ready to help you accelerate your data modernization journey.

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