Aster.
A retrieval database that makes your business data AI-ready, at scale.
The data layer AI can actually use.
Every AI project hits the same wall: the model is fine, but the data is a mess, scattered, duplicated, uncategorised, and impossible to retrieve reliably. Aster is the fix. It’s a retrieval (RAG) database built for large retrieval systems, where getting the right information back, every time, is the whole job.
Aster centralises, cleans, and categorises your business data so AI can use it, turning the pile you already have into something an agent can read across with confidence.
steps from scattered to retrievable
Centralise · Clean · Categorise
governed source of truth
Per-customer, permissioned
forced migrations to start
Works with what you have
From scattered to retrievable.
From scattered to retrievable.
Centralise
Pull data out of the dozen systems it's scattered across into one retrieval layer, without forcing a migration first.
Clean
Resolve duplicates, fix the mess, and reconcile the contradictions, the work that quietly breaks every AI project.
Categorise
Structure and tag everything so retrieval is accurate and permissioned, not a keyword guess across a pile of files.
Deployed inside Iris.
Aster is the data core at the centre of the system: deployed inside Iris so the operating system and the agents running on it draw from one clean, governed source of truth.
Spin up a workspace first.
Open a free Nomad Portal workspace, set up your own AI seats, and connect your tools — then bring in Aster when your data needs to become something AI can actually retrieve. We help you get set up; we don't resell seats or take a cut.
Make your data AI-ready.
A 30-minute call about the data you're sitting on, and what it would take to make it retrievable.
Talk to us →