Capability 01

AI & Data Engineering

From AI experiments to AI in production.

Generative AI integration, enterprise AI platforms, and the data engineering foundations that make them work. We help customers move from AI experiments to AI in production — with the data pipelines, governance, and operational practices that real-world AI requires.

Service lines

What we deliver under AI & Data Engineering.

01

AI & Generative AI

Designed, deployed, and operated GenAI systems for enterprise workloads — including agentic systems, RAG architectures, and AI copilots integrated into existing business processes.

What we deliver

  • Generative AI integration and applied use-case development
  • Agentic AI design and orchestration
  • Retrieval-Augmented Generation (RAG) architectures
  • Enterprise AI platforms — design, build, and operate
  • LLM infrastructure deployment and fine-tuning
  • AI copilots and process automation
  • AI orchestration and workflow systems
  • AI governance, evaluation, and compliance

Typical use cases

Internal AI copilots for customer service and sales · Agentic systems for back-office automation · RAG over enterprise knowledge bases · LLM deployment for sovereign workloads

02

Data Engineering & Analytics

The data foundations that make AI work — and that make traditional analytics finally deliver. Big data platforms, real-time pipelines, MLOps, and the governance layer that ties them together.

What we deliver

  • Big data platforms — Spark, Databricks, Snowflake, BigQuery
  • Data lakes and data warehouses — design, migration, modernization
  • Real-time analytics and streaming pipelines
  • Predictive analytics and machine learning models
  • Business intelligence dashboards and self-service analytics
  • MLOps pipelines and model lifecycle management
  • Data governance, lineage, and quality frameworks
  • Master data management and data observability

Typical use cases

Migrating from on-prem warehouses to cloud platforms · Building real-time pipelines for fraud detection · MLOps for production ML at scale · Self-service BI rollouts

Talk to an AI & Data specialist

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