DDataballastby Arrochar Labs
Interactive demo availableIn development · early access

Data ready for AI, at scale.

Databallast turns your data estate into a governed, AI-ready asset - the ballast that keeps the AI ship stable.

A shared business language, mapped and certified data, and DAMA-aligned governance that keeps every AI grounded in data it can trust - use case after use case, as the estate grows.

Why Databallast

AI doesn't fail on models. It fails on data.

Every serious AI initiative lands on the same blockers: no shared business language, no clear picture of what data exists or who owns it, and no way to say whether a dataset can legally and safely be used by an AI. Generative AI amplifies data debt - an ungoverned data estate becomes an ungoverned AI estate.

Data catalogs and governance programs exist, but none of them answer the question boards now ask: is our data actually ready for AI? Databallast is built around that question. Getting one dataset ready for one model is a project - keeping the whole estate ready, use case after use case, is an operating capability. That capability is the product.

How it helps your organisation

One business language for people and AI

A governed business glossary and logical business information model give your organisation - and your AI - a single, approved meaning for every term.

Know your data, end to end

A living catalog of datasets with ownership, classification, quality and lineage - including which AI systems consume which data.

Certify data AI-ready

Every dataset is assessed for rights and licensing, privacy, quality, freshness, bias, documentation and retrieval-readiness - and earns an AI-Ready mark a CDO can stand behind.

Governance as an operating capability

DAMA-aligned stewardship, policies, quality rules and issue management - plus a maturity assessment that shows the board measurable progress.

The differentiator

Eight checks. One AI-Ready mark.

Every dataset an AI touches is certified across eight checks and re-certified as data and rules change - the artefact auditors, boards and the rest of your AI stack consume.

Rights & licensing
Consent & privacy
Quality thresholds
Freshness
Bias & representativeness
Documentation
Lineage completeness
Retrieval-readiness

What it does

The full DAMA-aligned data-management stack, built explicitly for AI use - for Chief Data Officers, data governance and architecture leaders, and AI leads who need their data estate ready for AI, and provable.

Ground - the data pillar of Arrochar Labs' Accountable AI Framework, grounding every stage of the lifecycle in data AI can trust.
  • Business glossary with approval workflow and AI-context annotations
  • Metadata catalog, classification and data lineage
  • Logical business information model mapped to glossary and datasets
  • DAMA-DMBOK data maturity assessment with uplift roadmap
  • Data products and AI use cases with readiness gating
  • DAMA-aligned governance: stewardship, policies, quality rules, issues
  • AI-readiness certification per dataset (rights, privacy, quality, bias, retrieval)
  • Feeds Execdive's semantic layer, Meshbone data dependencies and Orbit roadmaps

See it on a real data estate

A clickable walkthrough of the Databallast workspace, seeded with realistic data for a 900-staff Australian water utility preparing 42 datasets and four AI use cases - glossary to AI-readiness certification.

Demos are approved individually and run on realistic sample data only.