AI & Data · Build

Data you can trust, and reporting your people will act on.

In most AI projects the model is the easy part and the data decides the result. We join your ERP, CRM, commerce and portal data on a reliable key, build the reporting your people act on, and lay the foundations AI depends on.

Talk to usStart with an AI assessment
Where your data stands

Five data positions, and what each means.

Every AI opportunity depends on data in one of five positions. The position doesn't decide whether it can be done; it decides what comes first.

  • Low dependency

    The job needs little of your own data, such as drafting or summarising. Ready now.

  • In hand

    The data exists in one system, such as your ERP, in a usable form. Ready soon.

  • Siloed

    It exists, but across systems that don't share a key, such as CRM, ERP and spreadsheets. The join comes first.

  • Partial

    Some of it exists, with gaps in history, coverage or quality. Fill the gaps, or start smaller.

  • Absent

    It isn't captured yet. A data foundation comes before any AI.

What we do

From scattered systems to one view.

  • The join, and its key

    ERP, CRM, EPoS and commerce data joined and kept in sync. We start by matching records across them, so you know how many line up cleanly before anything is built on them.

  • Business-intelligence portals

    Your data structured and analysed in a meaningful way, for fact-based decisions.

  • Product and catalogue data

    Clean, enriched product information that search, merchandising and AI assistants can use.

  • A boundary on what AI sees

    Each person's questions answered only from what they're allowed to see, and nothing passed to a model that it doesn't need.

The right tool for the job

Not every data problem is a language-model problem.

  • Language models

    For reading and writing at scale. Answering questions from your documents, reading emailed orders and specifications, drafting product content.

  • Specialised models and plain code

    For numbers and rules. Demand forecasting, anomaly detection, classification, pricing and optimisation, where a language model is the wrong tool.

Our work

Data joined up in practice.

All case studies

How we work

Plan. Build. Govern.

  • Plan

    Where AI pays, and in what order. For a whole business, the PureNet Group's Converge Methodology; for a single area, a fixed-scope assessment.

  • Build

    A pilot with a number to move, an owner and a way to stop it, then production in your storefront, portal and back office, integrated with your ERP and CRM.

  • Govern

    Govern the use, not the technology. Your own AI on business terms, with an owner, a one-page policy and an inventory; and every system we build for you tested on every change, logged, overseen by a person and fitted with an off switch, under our ISO 27001 controls.

Questions

What people ask us.

Do we need clean data before we start with AI?

No. Some opportunities need little of your data and can start now. For the rest, knowing each one's data position tells you what to fix first, so the foundations start early rather than holding everything up.

How do you find out how good our data is?

From the people who work with it and by testing it. We match records across your systems on a common key and report how many line up cleanly, which is quicker and more honest than a long audit.

Is our data safe?

Each job gets only the data it needs, answers respect each person's permissions, and your data is handled under our ISO 27001 controls.

Can AI forecast our demand?

Yes, but usually not with a language model. Forecasting, anomaly detection and optimisation are jobs for specialised models or plain code, and we use the right tool for each.