Make your enterprise data safe, visible and ready for AI
ETT helps organisations discover, classify and prepare structured and unstructured data for AI deployment. We help you understand what data you have, where it lives, how sensitive it is, and what needs to be improved before it can support trusted AI systems.
Why this matters
Most enterprises want to use AI more effectively, but many are starting from a difficult position.
Their data is spread across cloud platforms, legacy systems, data lakes, shared drives, spreadsheets, emails, documents, transcripts and custom tools. Some of it is structured. Much of it is not. Some of it is sensitive. Some of it is duplicated, outdated or poorly labelled.
Without a clear view of what data exists and how it should be handled, AI becomes harder to trust.
ETT helps organisations create that visibility. We discover where data lives, classify it by sensitivity and business function, and prepare it so it can be used more safely and effectively inside AI systems.
Why discovery and classification come before AI deployment
AI systems need reliable data, but reliability starts with knowing what data the business actually holds.
If sensitive information is hidden in unstructured files, customer records are inconsistent, internal knowledge is scattered or data ownership is unclear, AI systems can introduce risk quickly. They may surface the wrong information, expose data that should be protected, or operate from sources that are incomplete or poorly understood.
Discovery and classification create the control layer that AI needs. They help organisations identify what data can be used, what needs protecting, what requires cleaning and what should not enter an AI workflow at all.
Hidden sensitive data, unclear ownership, inconsistent records, unstructured sources, higher AI risk.
Known data estate, clear labels, sensitivity mapping, AI-ready sources, stronger governance.
How we help
Data discovery
We scan and map data across cloud apps, data lakes, legacy systems, shared repositories and operational platforms, creating a clearer view of where data lives, how it is used and what may be hidden.
Structured and unstructured data mapping
We identify and organise both structured data, such as databases and system records, and unstructured data, such as documents, emails, transcripts, call logs and knowledge files.
Data classification
We classify data by sensitivity, compliance category, business function and potential AI use case, helping organisations understand what can be used safely and what needs additional controls.
Sensitive data identification
We help identify data such as PII, PHI, customer information, financial records and sensitive business data before it enters AI workflows.
Data structuring and metadata enrichment
We support the deduplication, normalisation and enrichment of data with the context and metadata needed for AI systems to use it more effectively.
AI readiness preparation
We help prepare data for use in AI workflows, including grounding, retrieval-augmented generation, knowledge repositories, vector databases and semantic relationships where appropriate.
Who this service is for
CISOs and security leaders
Understand where sensitive data lives and how it could be exposed through AI systems.
Data leaders
Build clean, structured and reliable data foundations for AI, analytics and automation.
IT leaders
Manage fragmented systems, legacy platforms, cloud apps and data estates that have grown over time.
Compliance teams
Prepare for AI governance, audits, privacy reviews or regulated data use.
AI and machine learning teams
Get reliable training, grounding or retrieval sources before AI systems can perform effectively.
How we prepare enterprise data for AI
Diagnose
We identify where data lives, how it is currently used, what systems are involved and where hidden or sensitive data may create risk.
Design
We define the classification approach, data handling rules, metadata structure, AI readiness requirements and governance considerations.
Deploy
We apply discovery, classification and structuring processes across the agreed data sources, creating clearer visibility and more usable AI foundations.
Operate
We help maintain data visibility over time, review classifications, update governance rules and improve readiness as AI use cases evolve.
What sets this apart
ETT does not treat data discovery as a box-ticking exercise.
For AI to work safely and reliably, data needs to be understood in context: where it lives, how it moves, who uses it, what it contains and how it may affect downstream AI systems.
We help organisations connect data discovery and classification to the wider AI journey, from strategy and governance through to automation, grounding and live deployment. This means the work is not just about finding data. It is about making data usable, secure and ready for the AI systems that depend on it.
Built around AI readiness
We focus on the data conditions needed for safe and effective AI deployment.
Structured for governance
Classification helps organisations understand sensitivity, ownership, compliance and usage boundaries.
Connected to real use cases
Data preparation is shaped around the AI workflows, models and automation use cases the business wants to support.
Designed for ongoing control
Data estates change over time, so classification and readiness need to be maintained as AI adoption grows.
Often delivered alongside
Common questions
What is data discovery for AI?
The process of locating and mapping the data an organisation holds, including structured and unstructured sources, so it can be assessed for AI readiness, governance and safe use.
What is AI data classification?
Labelling data by sensitivity, compliance category, business function and potential AI use case. This helps organisations decide what data can be used, protected, restricted or excluded from AI workflows.
Why is data classification important before using AI?
AI systems may access, retrieve or act on business data. Classification helps prevent sensitive, inaccurate or inappropriate data from being used in ways that create risk.
What types of data should be discovered and classified?
Databases, documents, emails, transcripts, call logs, spreadsheets, customer records, internal knowledge bases, cloud app data and legacy system data.
How does data discovery support RAG and AI grounding?
Discovery helps identify which sources can be used for retrieval-augmented generation and grounding. Classification and structuring then make those sources more reliable, traceable and suitable for AI use.
Do you know what data your AI will rely on?
Book an Executive AI Acceleration Session to explore whether your data estate is ready for AI, where hidden risks may exist, and what needs to be discovered, classified or structured before deployment.