Streamlined Data Analysis

Intuitive Data Workflow Approach

Our approach builds on years of experience and a deep understanding of real-world data workflow challenges.

We deliver flexible, scalable, and future-proof workflows that integrate seamlessly into existing environments — replacing static, manual solutions with sustainable automation.

The Omics Data Analysis Quality Charter

Every omics data workflow at Data Intuitive is built on principles that ensure scientific integrity, reliability, and lasting value. These principles define how work is carried out, how results are shared, and how analytical systems continue to deliver value over time.

Click the cards below to explore each principle in more detail.

Standards & Best Practices

Automated code generation replaces ad-hoc development, enabling the orchestration of structured, modular workflow components that reduce friction and human error.

Consistent, high-quality analytical modules establish best practices, transforming complexity into clarity and making workflows easier to understand, maintain, and extend.

Reproducibility & Scientific Integrity

Every analysis can be traced, repeated, and trusted — from a simple transformation to fully scalable, end-to-end omics workflows.

Analyses run consistently across research and production environments, ensuring scientific integrity and regulatory confidence.

Compliance & Governance

Version control, auditable metadata, and automated documentation ensure regulatory readiness, full ownership, and accountability.

Each workflow is a versioned, extensible asset whose intellectual property remains under organizational control.

Efficiency & Computational Scalability

Analyses execute and scale seamlessly across local machines, HPC clusters, and cloud infrastructures with minimal effort.

Scientists can focus on analysis and discovery, while a secure platform manages usability, orchestration, and operational consistency from development to production.

Collaboration & FAIR

Our approach eliminates silos, preserves institutional knowledge, and fosters collaboration across teams and organizational boundaries in a governed manner.

The platform ensures that workflows and their components are Findable, Accessible, Interoperable, and Reusable (FAIR) — whether open or securely managed in private environments.

Long-Term Value

Our workflows are built from modular components that evolve with scientific and operational needs, supporting new omics technologies and system evolution.

All workflows are designed to minimize dependence on individual experts, specific vendors, or proprietary technologies — a key factor in a rapidly changing technology landscape.

Viash Catalogue

The open-source Viash Catalogue offers a comprehensive collection of publicly available bioinformatics data workflows and modules. They are ready for stand-alone use or integration into larger data workflows.

Viash Hub

Viash Hub is a platform for managing, deploying, and sharing bioinformatics modules and workflows.

It allows users to publish, share, and maintain versioned modules, ensuring reusability and easy access following the FAIR principles.

Optimised for cloud and HPC environments, it simplifies launching data workflows.

Viash

Viash is the open-source tool developed by Data Intuitive to manage, deploy, and share data workflows. It automates the generation of modular, executable components, ensuring that workflows are reproducible, scalable, and easily integrated into various computational environments.

Engineered with deep expertise in Nextflow pipelines, Viash minimizes manual boilerplate coding, significantly boosting maintainability and reducing errors.

Approach