Enterprise Data & AI Platforms

Unleash the potential of your data.
Let's turn it into a business driver.

Value from data & AI,
built on solid foundations

We help build data and AI platforms where ownership is clear, compliance is manageable and your teams can launch and scale new solutions without starting from scratch. One foundation built to grow with your ambitions.

Our Data & AI Services

No matter where you are on your data journey, we focus on solutions that bring real value: not one‑size‑fits‑all. Strong data work starts with the right governance and architecture so your organization can extract meaningful value from the get-go. And with the right foundation, your data capabilities can grow and evolve today, and support tomorrow’s needs.

Data & AI Governance

Strong Data & AI platforms start with governance that supports the use and growth of the platform itself, with trusted and reusable managed assets. Data products help, but they’re not the only tool. We help you build governance that drives value while keeping data safe and compliant.

What we deliver

Data governance frameworks and operating models
Ownership models and domain-aligned responsibilities
Data product identification, design, and lifecycle management
Discoverable, cataloged and trusted data
Data quality measurement, monitoring, and remediation
Compliance, access controls, and privacy management

Business outcomes

Ensuring teams can work independently in a controlled manner
Projects can concentrate on creating value, not finding data
Data that gets reused, not rebuilt. New use cases in weeks instead of months
Know what data you have, where it comes from, and who owns it
Compliance and data quality without constant firefighting
Data that's AI-ready from the start

Data Platforms

A strong Data & AI foundation needs a modern platform that can support your use cases and run AI/ML at scale. We design and build platforms using the right technologies and architecture for your goals, helping you grow, modernize, and get more value from your data today and tomorrow.

What we deliver

Right technology (Databricks, Snowflake, Fabric)
Right data management principles (Data Mesh or other)
Platform architecture and implementation
Data modeling and design
Data integrations across systems
Scalable, cloud-native data infrastructure

Business outcomes

Trusted, governed data
Less complexity and risk
Ready for AI and analytics from day one

AI & ML Platform Capabilities

AI only creates value when it runs reliably in production and on top of your own data. We help you deploy and develop AI and ML capabilities and technologies that make development, and deployment practical and safe.

What we deliver

Built on top of your data foundation, using Databricks, Snowflake, Azure ML/AI Foundry, AWS Bedrock, SageMaker, or custom setups.

Expanding your platform architecture and implementation to support AI/ML
Scalable, reproducible development and training environments
Reliable, cost-effective production deployment and inference

Business outcomes

Faster time from idea to impact
AI solutions that reach production
AI that scales beyond the first experiment

Real-Time Data Ingestion Architecture

Batch processing gets you far, but some decisions just can't wait until tomorrow. When your business needs to react in minutes and not hours, you need data infrastructure that moves at the speed of events.

What we deliver

From streaming ingestion to real-time analytics, built on Kafka, Flink, Databricks, Microsoft Fabric, Azure, or AWS, depending on what fits your stack and scale.

Event-driven architecture design and implementation
Streaming data ingestion and processing pipelines
Change data capture (CDC) and real-time integration
Real-time analytics, alerting, and decisioning
Hybrid architectures combining batch and streaming

Business outcomes

Decisions based on what's happening now, not yesterday
Systems that react to events instead of waiting for reports
Real-time data that feeds both operations and analytics
A scalable path from batch-first to event-driven without ripping out what works

Getting value from your use cases

When you have your foundations in place, it’s time to enrich the data into information and actionable outcomes. We help you realize the value of your data use cases using DataOPS and AI and MLOps, ensuring high quality delivery and maintainability of the deliveries. If you want to have your own teams realize your use-cases, we offer training and expert support to help them show success at scale.

DataOps

One team can ship pipelines on talent alone, but scaling requires shared practices, automation, and a platform that makes doing things right easy. DataOps adds engineering discipline—CI/CD, testing, environments, and observability—so data work scales safely. We help you build the tooling and ways of working that make it stick.

What we deliver

CI/CD automation and workflow for developer teams
Data observability and reliability engineering
Standardized templates, patterns, and git practices

Business outcomes

Data teams that ship faster with higher reliability
New teams onboarded in days
Ownership that scales beyond a central data team
A platform that makes the right way the easy way

AI and MLOps

Just like with Data, ML models and agents need a solid development framework to stay stable in production and let teams focus on improving models, not firefighting. We build these foundations on Azure, AWS, Databricks, Snowflake or custom stacks—it's part of how we deliver every project, so we know what works.

What we deliver