Skip to main content
Contact Us
AI Services AI Data ReadinessCompare with another offering

AI Data Readiness

Our data isn't ready for the AI we want to run

Fix the data behind your priority AI use cases with an AI-ready data layer you can reuse for the next ones.

In brief

AI Data Readiness is a Kalosys service that checks whether the data behind one or two priority AI use cases is complete, current, accessible and governed. It then fixes the gaps by building a reusable, AI-ready data layer with quality rules, shared definitions, retrieval and access controls. It starts with a fixed-fee assessment.

THE PROBLEM

Why this matters now

AI use cases fail most often on data: it is scattered across systems, inconsistent, hard to reach securely, or understood differently by each team. Until that is fixed, pilots stall and agents give answers nobody trusts.

63%

of organizations don't have, or aren't sure they have, the right data management practices for AI

Gartner survey of 1,203 data leaders, Feb 2025

60%

of AI projects without AI-ready data will be abandoned through 2026

Gartner prediction, Feb 2025

HOW IT WORKS

Start small, prove value, then run it

Most AI projects that stall do so because of the data, not the model. The data is spread across systems, inconsistent, hard to reach securely, or defined differently by each team. We start from one or two use cases you care about, check whether the data behind them is ready, and fix the gaps by building an AI-ready data layer you can reuse for the next use cases.

01 · Fixed fee

Assess

  • Start from one or two target use cases
  • Find the data they need and where it lives
  • Check quality, access, ownership and shared definitions
  • Review privacy and security for data the AI will see

YOU RECEIVE

  • Data readiness scorecard per use case
  • Gaps ranked by impact
  • Data-layer roadmap and fixed-price build proposal
  • Recommendation to proceed, defer or stop

02 · Fixed scope

Build

  • Integrate priority sources into an AI-ready data layer
  • Quality rules and shared business definitions
  • Vector store and retrieval for AI use cases
  • Access controls and lineage

YOU RECEIVE

  • Working data layer for the target use cases
  • Data quality rules and glossary
  • Access and lineage documentation

03 · Monthly

Run

  • Pipeline monitoring and data quality alerts
  • Onboard new sources and use cases

YOU RECEIVE

  • Monthly data quality report

SCOPE AT A GLANCE

What's included, and what isn't

Included

  • One or two named AI use cases and their source data
  • Quality, access, ownership and definition checks

Not included

  • Fixing the data, which is the Build step

Done when

Each data gap behind the use case is measured, owned and prioritized.

OUTCOMES

What you get

  • AI built on data the business trusts
  • A faster path from pilot to production
  • Secure, governed access to the data AI uses
  • A reusable foundation for the next use cases

IS THIS FOR YOU?

You may need this if

  • Pilots blocked or unreliable because of data
  • Data spread across many systems
  • Teams disagree on definitions or numbers
  • Plans to use AI on internal documents

QUESTIONS

What leaders usually ask

Do you replace our data platform?

No. We work with your existing platform and add what AI needs on top of it.

What is a vector store?

A database that stores text and documents in a form AI can search by meaning, so an assistant can find the right policy, contract or ticket to answer a question.

Have you built this before?

Kalosys built and runs its own AI data layer on AWS Aurora PostgreSQL with pgvector, which is the reference design for this offering. We can share more detail.

We already have a data warehouse.

That's a strong starting point. AI needs some things a reporting warehouse usually doesn't have, like document content, shared definitions, retrieval for AI and access controls at a finer level. We extend what you have rather than replace it.

Our data team is already busy.

That's common, which is why we scope to one or two use cases instead of a full data program. The assessment shows exactly what has to change and what doesn't.

Can't the AI just work with messy data?

It will produce answers, but people stop trusting them quickly. Fixing the data behind the first use cases is usually what decides whether AI gets used or quietly abandoned.

RELATED

Often paired with

Pilot to Production"We've run pilots that never shipped."Agent Governance and Control"Who can stop an agent, and how fast?"AI Decision Review"Should we make this AI investment, and is it the right one?"

Not sure where to start?

Start with an AI Decision Review, or talk to us about AI Data Readiness. Every engagement starts with a fixed fee and a clear recommendation.

GET IN TOUCH

Talk to us about AI Data Readiness

Tell us what you are working on. A senior member of our AI team will get back to you within one business day.

Prefer to talk now? Talk to Alleria, our AI sales agent.

Last updated October 29, 2026