Node DATA.02

AI-ready data foundations

Clean, modelled, governed data, so AI systems give answers you can use.

Start a project Take the AI readiness scan

Cleaning, modelling and governing data so AI assistants, agents and models can use it: document pipelines, semantic layers, access controls and lineage.

The problem

AI projects fail quietly on data: duplicate customer records, outdated policy documents, fields that mean different things in different systems, and no record of who may see what.

Getting data ready for AI is different from getting it ready for a monthly report. Assistants need current, deduplicated documents with access metadata; agents need well-defined entities and actions; models need consistent history.

What we build

Document pipelines that collect, deduplicate, version and tag content for retrieval
Semantic layers and metric definitions that AI tools query instead of raw tables
Entity resolution for customers, products and suppliers across systems
Access controls and data classification that carry through to AI applications
Lineage, so any AI answer can be traced back to its source

How it works

Structured and unstructured sources are cleaned and resolved into governed datasets and document stores, with access rules and lineage that AI applications inherit.

Step 1Assess readinessScore your key datasets and document stores for completeness, freshness, duplication and access control.
Step 2Fix the foundationsDeduplicate, standardise and model the data the first AI use case needs.
Step 3GovernClassify sensitive data and define who and what may access it.
Step 4Expose for AIPublish a semantic layer, document index or APIs that AI systems use.
Step 5Keep it freshAutomate refreshes and quality checks so it stays ready.

Deliverables

Data readiness assessment
Cleaned and modelled datasets for the first use case
Data classification and access policy
Semantic layer or document index
Quality monitoring

Typical stack

Python
SQL
Snowflake
Google Cloud

We choose tools to fit your environment; this is where we usually start.

Ways to work with us

AI Strategy SprintA ranked roadmap and a working prototype, in a fixed scope.Engagement Build and HandoverA defined system, delivered, documented and handed to your team.Engagement Forward Deployed EngineersOur engineers inside your team until it runs in production.Engagement

Questions

Do we need to fix all our data before starting with AI?

No. We fix the data the first use case needs, then extend. Waiting for perfect data everywhere means never starting.

How do you handle personal data?

We classify it, restrict access, and minimise what reaches AI systems. Data protection obligations, including India's DPDP Act, are considered in the design.

Adjacent nodes

Part of Data.

Data engineering and modern data platformsPipelines and a warehouse your team stops arguing about.DATA.01 AI assistants and chatbotsAssistants that answer from your documents and data, and say when they do not know.AI.02 AI governance and responsible AIClear rules for how your organisation uses AI, that people actually follow.ADV.02

Talk to us about aI-ready data foundations for your business.

Send a short brief. We reply by email, usually with questions before we propose anything.