— Technology we master

Apache Spark

The distributed analytics engine for processing terabytes.

Spark processes massive data volumes in-memory across a distributed cluster. Its APIs (DataFrame, SQL, Streaming, MLlib) cover batch, stream and machine learning. Coupled with Delta Lake, it's the foundation of modern lakehouses.

Why Apache Spark

What Apache Spark brings to your project.

Typical use cases: Large-volume ETL, lakehouse, distributed ML training.

  1. 01

    In-memory distributed processing: orders of magnitude vs Hadoop.

  2. 02

    Python, Scala, SQL, R APIs: heterogeneous teams accommodated.

  3. 03

    Structured Streaming for near-real-time processing.

  4. 04

    Databricks, EMR, Dataproc: managed across three clouds.

Our AI stance

AI-augmented approach, supervised by experts.

We use artificial intelligence as a lever for acceleration and optimisation within our technical processes, while keeping strong human oversight on every strategic phase of the project.

AI improves productivity. It does not replace:

  • field experience
  • architectural expertise
  • understanding business stakes
  • technical governance
  • complex trade-offs
  • cybersecurity
  • operational accountability

Beyond visual and technical design, as well as AI-augmented programming, our teams act as a layer of validation, quality control, security hardening and steering, to ensure reliable, scalable deliverables that can operate in real-world environments.

Free quote · no commitment

Let's discuss your project.

Describe your project. Our team replies within 24 hours with free technical scoping, along with a clear estimate of costs and timelines. No commitment.

  • Reply within 24 hours from a project manager
    or engineer.
  • Technical scoping and quote, with no fees.
  • No commitment, your data stays
    confidential.
Quick estimate

Free scoping & estimate in under an hour

Describe your project and we'll get back to you with a costed estimate and a roadmap.

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