What does "AI ready" data actually mean?

AI ready data is accurate, complete, current, and well described, so an AI tool can find it, understand it, and use it correctly. It also needs the right permissions applied, so AI tools only surface information to people who are allowed to see it.

What parts of the data journey can PTR help with?

PTR supports the full data lifecycle: collecting, storing, preparing, and serving data for analytics and reporting, whether it be BI or AI.

Can't we just switch on an AI assistant and see what happens?

You can, and many organisations do. The risk is that tools such as Microsoft 365 Copilot, ChatGPT, Claude, and Gemini surface whatever they can access, including out of date documents, duplicated data, and files with overly broad permissions. A short readiness assessment first is usually far cheaper than unpicking the consequences afterwards.

How do organisations keep data secure while enabling BI and AI?

There are a number of features and services that help to keep data secure and compliant: - Role-Based Access Control (RBAC) - Row-Level and Object-Level Security (RLS/OLS) - Encryption - Data loss prevention (DLP) - Governance tools auch as Microsoft Purview - Auditing and monitoring Security must be continually reviewd and solutions must evolve as data volumes and AI use cases expand.

How long does it take to get our data AI ready?

It depends on where you are starting from. An AI Readiness Assessment typically takes 3-5 days and gives you a prioritised plan. Many organisations then start with one well chosen use case and get its data foundations right first, rather than trying to fix everything at once.

How does AI change the way organisations manage data?

AI consumes extremely high volumes of high‑quality, labelled data. To ensure quality, trustworthy data organisations must focus on: - Metadata and lineage tracking - Bias detection - Model-ready datasets - Continuous monitoring for data drift - Stronger privacy and compliance controls

What is an ontology, and why does AI need one?

An ontology describes the things your business cares about, such as customers, products, sites, and orders, along with how they relate and the rules that apply to them. It gives AI agents a shared understanding of your business, so they reason about "a customer with an overdue order" rather than guessing at table and column names. In Microsoft Fabric, ontologies are built in Fabric IQ and can be generated as a starting point from the semantic models you may already have.

AI Readiness & Data Foundations

What is AI Readiness?

AI readiness means having the data, processes, and controls in place before AI tools can be trusted to work on your behalf. Most of that comes down to your data foundations: data that is collected from the right systems, moved and refreshed reliably, checked for quality, organised so it carries real business meaning, and governed so the right people (and the right AI tools) can see the right things.

It is tempting to start with the tool. Switch on Microsoft 365 Copilot, give everyone ChatGPT, Claude, or Gemini, try out an AI agent. But AI tools don't fix data problems, they amplify them. An AI assistant grounded in out of date documents gives confident, out of date answers. An agent working from duplicated customer records acts on the wrong customer. A model trained on incomplete history makes incomplete predictions, and does so very convincingly.

The stakes rise as AI moves from answering questions to taking action. AI assistants and Fabric data agents need trusted data to give good answers. AI agents and automated workflows that act on your behalf need more than that: a shared understanding of what a customer, an order, or an asset actually means in your business, and the rules that apply to each. That shared understanding is called an ontology, and with Fabric IQ it can be modelled directly over your data in OneLake, ready for agents to reason over.

The good news is that the work needed to get AI ready is the same work that makes everything else better too. Reliable pipelines, trusted data, and clear governance improve your reporting and your decision making today, and they give you a platform you can confidently build AI on tomorrow. Get the foundations right and AI becomes an asset. Get them wrong and it becomes an expensive way to make mistakes at scale.

How can PTR help?

AI Readiness Assessment

Evaluate where the gaps are in your data and governance first, so you get the foundations right for any Artificial Intelligence (AI) or Machine Learning (ML) endeavours.

Data Engineering & Integration

Our data engineers will help you extract data from myriad sources and prepare it for consumption by a whole range of different workloads.

Data Quality & Governance

Make sure the data your AI relies on is accurate, secure, and fit for purpose, with quality checks that catch problems early and Microsoft Purview policies that control who, and what, can see it, so AI assistants never surface content they shouldn't.

Business Ontology & Semantic Models

Teach AI what your data means. We model your business concepts, relationships, and rules as semantic models and Fabric IQ ontologies, then make them available through MCP, so any AI tool reasons in your language, not in table names.

Documents & Knowledge

Turn documents and shared drives into a curated, current knowledge source, with the indexing pipelines that let AI assistants and agents find the right answer and show where it came from.

Document Intelligence

Unlock the data trapped in PDFs, forms, invoices, and emails by automatically extracting it into structured, validated data that feeds your systems, automated workflows, and AI agents.

Process Automation & Agentic AI

Automate repetitive tasks and free up your time to focus on the things that are really going to make a difference to your business.

AI Data Access

Give AI assistants and agents secure, governed access to your data through MCP servers and APIs, so every tool works from the same trusted source, with your permissions and audit trail intact.

AI Enablement

Help your people use, oversee, and trust AI tools, with training and coaching that builds AI literacy, good habits, and the human checkpoints that keep AI working for you.

Technologies

We specialise in building data solutions in the Microsoft ecosystem. We have been a Microsoft partner since 2005, currently holding Solution Partner designation for Data & AI in Azure, with certifications held across the team in Microsoft Fabric, Azure, and Power BI so you can be confident that our knowledge and skills have been tried and tested.

Microsoft Fabric

Microsoft Fabric is a unified analytics platform, an evolution of several existing Microsoft analytics products consolidated into a single administrative environment and licensing model which makes licensing, development, and administration much simpler.

Microsoft Azure

Azure is a public cloud offering from Microsoft. With an ever expanding marketplace of components and services available, you can build tailor made data platform solutions precisely to your specification.

Microsoft Copilot Studio

Build, customise, and deploy your own copilots and AI agents, grounded in your business data and connected to the systems your people use every day.

Microsoft Foundry

Design and run bespoke, enterprise-grade agentic solutions, combining large language models with your own data, orchestration, and the controls to deploy them safely at scale.

Microsoft Purview

Microsoft Purview helps organisations understand, protect, and govern their data wherever it lives.

Crucially, good foundations are not tied to any one AI tool. The same trusted data, semantic models, and ontology can serve Microsoft 365 Copilot, agents built in Copilot Studio or Azure AI Foundry, ChatGPT, Claude, Gemini, or an application of your own. More and more of that connection happens through the Model Context Protocol (MCP), an open standard that lets any compatible AI tool discover and use your data in a governed way. Microsoft Fabric already makes data agents and Fabric IQ ontologies available through MCP, so you can build your foundations once, then choose, combine, or change your AI tools as the market moves.

Why choose PTR?

We have been helping our clients for over 35 years, getting data of all shapes and sizes out of hundreds of different systems and into a state people can rely on. That experience matters more than ever now that AI tools are consuming the same data. We take the time to listen and learn everything we can about you, your business, your people, your data estate, and your aspirations, then build practical, scalable foundations that let you adopt AI at your own pace, with confidence that it is working from data you can trust.

How do we work with you?

Whether it's purely strategic advice, implementation and development work to spec, fractional data engineering support, or a fully outsourced data function, we offer a range of flexible engagement patterns to suit your business, budget, and need.

Pay As You Go

DAY RATE

£1,250/day or £200/hour

Flexible delivery as and when you need it

No Commitment
Time and Materials
Use us when you need us

Fixed Project Fee

PRICE

£On Request

Everything locked in up front

Fixed Deliverables
Fixed Fee
Clear timescales

Retained Service

FROM

£1,095/month

Cost effective and flexible resource augmentation

12 Month Agreement
Minimum 1 day/month
Discounted day rate
Predictable monthly billing
Flexible delivery
Easy top-up
Discounted training

AI Foundations work pairs naturally with our blended engagements, which combine strategic advice and consultative delivery with training, so your people learn to use and oversee AI tools as the foundations go in.

What does this look like for you?

1 Hour - An introductory call with one of our solution architects to learn about your requirements and help us identify the best next steps for you.

Typically 3-5 days - A deep dive into your data estate, platform, governance, and people, measured against the AI use cases you have in mind. You come away with a clear picture of where you stand and a prioritised plan for getting AI ready.

Typically 5 Days - Particularly with larger projects, it is useful to demonstrate the technical feasibility and business value of a project before committing to long term spend. Not always necessary, but can help to firm up some variables and to measure consumption demands which can be difficult to predict in cloud environments.

Typically 10-20 Days - This really will be different for everyone and can vary widely, but we aim to work in short cycles that deliver quick results with scope for iterative onward development and flexibility to change requirements.

Typically 3-5 Days/Month - Once people get an appetite for data, it tends to keep growing and with it, requirements keep evolving. Our retainer service enables you to keep a highly skilled data team on hand to respond to those changing requirements under a predictable billing model to suit your budget.

Free Discovery Workshop

AI Readiness Assessment

Proof of Concept/Value (PoC/PoV)

Minimum Viable Product (MVP)

Retained Consultancy Service

AI Readiness & Data Foundations Consultancy Services