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Nekt is a data infrastructure platform that replaces fragmented tools, scripts, and spreadsheets with a single environment where your team can connect, organize, and activate data — for dashboards, automations, and AI agents alike. Nekt can run directly in your cloud environment or in Nekt Express, our hosted environment. Either way, your team gets a unified platform to manage the entire data lifecycle.

Why Nekt exists

Most teams reach a point where data starts to spread across multiple systems:
  • SaaS tools and APIs
  • spreadsheets and exports
  • BI tools and dashboards
  • internal databases
  • AI tools and agents
Transactional databases keep your applications running, but they are not designed for analytics, historical tracking, or cross-system visibility. Without a dedicated data infrastructure, teams face:
  • inconsistent KPIs across tools and teams
  • no historical record of how data changes over time
  • manual data consolidation with no audit trail
  • ungoverned access — no control over who sees what
  • data silos that block collaboration and AI adoption
Nekt solves this by creating a governed data layer where all company data is extracted, organized, versioned, and made available for analysis and automation — with permissions, lineage, and history built in.

Core modules

Nekt is built around a set of modules that move data from source to activation.

Who uses Nekt

Nekt is used by teams that want to move faster with data without building a full internal data platform. This includes:
  • data teams that need reliable infrastructure
  • revenue and operations teams that depend on analytics
  • product teams building AI-powered workflows
  • companies that want structured data without heavy engineering effort
Some teams using Nekt have dedicated data engineers. Others do not. The platform is designed so that both technical and non-technical users can work with data reliably and independently.

Getting started

The fastest way to understand Nekt is to connect your first data source. From there you can:
  1. extract data from your systems
  2. explore it in the Catalog
  3. build Queries with SQL or Notebooks with Python
  4. activate the results in dashboards, automations, or AI agents
Continue to Getting Started to set up your first workspace.