AI Data Engineering Services: Modernize Enterprise Data 3x Faster
Build modern, AI-ready data platforms with AI-accelerated engineering. From legacy migration and ETL automation to cloud-native architectures, we help enterprises deliver secure, scalable, and high-performance data platforms with greater speed and lower risk.
Enterprise AI Data Engineering & Automation Solutions
Whether you are migrating a legacy Teradata or Oracle environment to Snowflake, Databricks, or Microsoft Fabric, building a new cloud-native data platform from greenfield inputs, or preparing your enterprise data foundation for generative AI and analytics workloads, we deliver production-grade results with the speed and accuracy that enterprise programmes require. See how this compares to traditional approaches in our RAG pipeline architecture and retrieval-augmented generation expertise page.
Our AI data engineering expertise and accelerator tools are available as standalone accelerator deployments for your team or as a fully managed end-to-end engineering engagement, depending on where your data programme needs the most support.
Why Traditional Data Engineering Fails Enterprise Programmes
Slow Development Cycles
Repetitive, manual pipeline coding leads to high maintenance costs.
Inconsistent Data
Manually created quality rules result in compliance risks and data drift.
Migration Headaches
Converting legacy stored procedures to modern stacks is error-prone.
Query Performance
Manually built, unoptimized data models lead to slow analytics.
Onboarding Delays & Duplicated Work
Undocumented pipeline logic and processes.
Deployment Bottlenecks & Quality Issues
Lack of standardized pipeline logic and repeatable processes.
Deliverables of AI-Augmented Data Engineering
3x Faster Data Script Development & ETL Automation
AI to generate, refactor, and optimize data scripts and transformation workflows.
Legacy System Modernization
Automatically decode undocumented SQL logic and convert legacy code (Teradata, Oracle) to modern stacks (Snowflake, PySpark).
Intelligent Data Modeling & Automated Lineage Tracking
Accelerate schema design, data mapping, metadata extraction, and lineage documentation using AI-augmented modeling tools.
Automated Data Platform Migration & Code Conversion
Convert and migrate legacy data codebases across platforms (Stored Procedures to PySpark, Teradata to BigQuery, Oracle to Snowflake).
End-to-End Data Pipeline Testing & Quality Automation
Auto-generate test cases, synthetic datasets, regression validations, and data quality checks for enterprise workflows.
Automated Data Documentation & Knowledge Management
Automatically generate and maintain pipeline documentation, transformation logic, data dictionaries, and technical specs.
AI Data Engineering Work We Have Delivered
Accelerating Data Migrations (Code Converter)
An intelligent AI agent with modular tools that orchestrates end-to-end SQL-to-PySpark conversion, automatically reading scripts, generating code, validating outputs, refining mismatches, and streaming results to engineers.
Intelligent Data Dictionary
AI Data Dictionary autonomously connects to databases, analyzes schemas, and automatically builds comprehensive data dictionaries with PII tagging, quality profiling, and human-readable documentation explaining each dataset's business relevance.
Fast Data Catalogue
Fast Data Catalogue is an AI-augmented platform that automatically discovers, documents, and explains enterprise data across any source, delivering comprehensive clarity and understanding in minutes instead of months.
Real-Time Social Media Sentiment Intelligence Platform
See how high-throughput data engineering pipelines process 2.3M+ daily signals with sub-second stream enrichment, multi-stage validation, and high-fidelity sentiment intelligence.
Industries We Serve
Healthcare
Clinical and claims data platforms, including a HIPAA-aligned build for a health insurer.
Legal
Structured, governed data pipelines for legal and case management systems.
Retail
Customer data unification, including a 1,600-table cataloging project ahead of a BigQuery migration.
Real Estate
Consolidated property and transaction data pipelines for real estate platforms.
Finance
Data migrations and Customer 360 platforms, including a Teradata-to-Snowflake assessment for a commercial bank.
Software Engineering
Reliable data infrastructure that powers product analytics and AI features.
Powered by Modern Data Platforms
Let's Modernize Your Enterprise Data Platform
From legacy migrations to AI-ready data platforms, we design and build secure, scalable data infrastructure that supports your business today and future AI initiatives.
Our Built Data Engineering Accelerators
Live, deployed tools used in production data engineering programmes. Each accelerator compresses a specific stage of the data engineering lifecycle that traditionally requires weeks of manual work.
Accelerating Data Migrations (Code Converter)
An intelligent AI agent with modular tools that orchestrates end-to-end SQL-to-PySpark conversion, automatically reading scripts, generating code, validating outputs, refining mismatches, and streaming results to engineers.
Intelligent Data Dictionary
AI Data Dictionary autonomously connects to databases, analyzes schemas, and automatically builds comprehensive data dictionaries with PII tagging, quality profiling, and human-readable documentation explaining each dataset's business relevance.
Fast Data Catalogue
Fast Data Catalogue is an AI-augmented platform that automatically discovers, documents, and explains enterprise data across any source, delivering comprehensive clarity and understanding in minutes instead of months.
Our AI-Accelerated Data Engineering Process
Discovery and Assessment
Source estate inventory, complexity scoring, target architecture design, and a delivery roadmap, delivered in 8 business days.
AI-Accelerated Migration & Code Conversion
AI-accelerated code conversion for stored procedures and ETL scripts, migrating from Teradata, Oracle, SQL Server, Synapse, Netezza, DB2, or SSIS to Snowflake, Databricks, Microsoft Fabric, BigQuery, or Redshift.
Data Modeling, Governance & Documentation
Schema design, PII tagging, quality profiling, lineage tracking, and human-readable data dictionaries built as the migration proceeds.
Automated Pipeline Testing & Quality Checks
Auto-generated test cases, synthetic datasets, and regression validation confirm accuracy at each migration wave before legacy systems are decommissioned.
Production Deployment & Team Handover
A production-deployed data platform, automated pipeline infrastructure, and a team enablement programme so your engineers can operate and extend it independently.
Frequently Asked Questions About AI Data Engineering Services
Everything you need to know about the services & billing.
Which legacy platforms can you migrate to Snowflake, Databricks, or Microsoft Fabric?
How long does an enterprise data platform migration or modernisation take?
What is the difference between ETL and ELT in modern data engineering?
Can AI data engineering services support generative AI and machine learning workloads?
What does GenAI Protos deliver at the end of a data engineering engagement?
Ready to Modernize Your Enterprise Data Platform?
Whether you're migrating legacy systems, building a cloud-native data platform, or preparing for AI workloads, we'll assess your environment, design the right architecture, and accelerate delivery.
