AI-powered platform automating legacy data warehouse migrations to modern cloud architectures

The Problem: Legacy Migration Crisis

Migrating corporate data warehouses from legacy platforms to the cloud is a multi-year, multi-million-euro nightmare. Companies face four critical challenges that drain resources and slow innovation.

Slow & Expensive Migrations

Multi-year timelines and massive budgets for moving from Teradata, Oracle, and Hadoop to modern platforms

Unpredictable Cloud Costs

Complex platforms like Databricks and Snowflake create billing spikes and misconfigured resources

Data Quality Blindness

Loss of visibility over data freshness, schema changes, and broken pipelines in complex stacks

GDPR Compliance Burden

Manual work tracking PII, applying masking policies, and proving compliance to auditors

The Core Pain Point

How do we quickly and safely move off legacy, build a modern data platform, and keep costs under control?

Most organizations operate a "zoo" of separate tools for migration, data quality, GDPR, and cloud costs. This fragmented approach is expensive, hard to integrate, and doesn't solve the fundamental challenge.

Our Solution: One Platform, Four Critical Layers

MorphData AI is a unified SaaS platform that covers the entire data lifecycle, eliminating the need for multiple point solutions.

AI-Powered Migration

Automatically translates legacy SQL/ETL code into dbt models, Spark pipelines, and modern SQL for Snowflake, BigQuery, and Databricks

Data Observability

Monitors freshness, anomalies, schema changes, and auto-generates quality tests using LLMs

Cloud Cost Intelligence

Analyzes logs, recommends optimizations, and predicts cost spikes based on workload patterns

GDPR Automation

Automatically detects PII, suggests masking strategies, and generates audit-ready compliance reports

How It Works: The Migration Engine

Intelligent Code Analysis

Our LLM-based engine doesn't just generate code from scratch. It analyzes thousands of legacy jobs and procedures, builds an abstract representation of transformation logic, and translates it to the target platform while preserving business logic and dependencies.

The system automatically builds data lineage and generates technical documentation, reducing key-person risk and accelerating onboarding.

01

Parse Legacy Code

Teradata, Oracle, Hadoop

02

Analyze Logic

Build abstract model

03

Generate Modern Code

dbt, Spark, SQL

04

Document & Deploy

Auto-generated docs

Market Opportunity

$25B

Global TAM

Conservative estimate for 2024, growing to $50B+ by 2030

$6B

European SAM

Mid-size and large enterprises operating under GDPR

$200M

3-5 Year SOM

France + DACH + Benelux focus on active migration projects

Competitive Landscape

ETL & Migration Tools

Players: Fivetran, Matillion, Talend, Informatica

Gap: Don't handle complex legacy code migration end-to-end or provide observability and FinOps


Data Observability

Players: Monte Carlo, Bigeye, Soda, Datafold

Gap: Don't automate migration or cover GDPR/PII deeply

Cloud Cost Management

Players: CloudHealth, Apptio, Flexera

Gap: Operate at infrastructure level, can't suggest pipeline changes


Data Privacy & GDPR

Players: BigID, OneTrust, Collibra

Gap: Not integrated with DWH/ETL optimization

Our Competitive Edge

End-to-End Platform

Unified horizontal layer across the entire data lifecycle, not a point solution

Code-Level Intelligence

Works at SQL query and ETL graph level, enabling automatic code rewriting and performance optimization

GDPR-by-Design

European focus with PII detection integrated into migration, not as an afterthought

Vendor-Agnostic

Strong focus on open-source (Spark, Airflow, dbt) and multi-cloud, reducing lock-in

Migration-First GTM

Entry through concrete migration projects with large budgets, then ongoing subscription revenue

Egor Tashchilov

Founder & CEO

Background:

  • 10+ years in data engineering and platform architecture
  • Led large-scale migrations: Teradata/Oracle → Snowflake/Databricks/BigQuery
  • Built data platforms with Spark, Airflow, Kafka, dbt
  • Hands-on experience with GDPR and PII anonymization

Growth Plan: Hire 1-2 senior engineers in France within 12-18 months, build local team of 5-10 within 3-4 years