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About
Services
Ozessa EngineAutomated ReconcilerCompute Cost ControlData Architecture AssessmentManaged Reliability
Calculator
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FAQ
Resources
Insights HubComprehensive GlossaryPlatform CompareSunday Tax ToolFabric Cost Tool
Book a consultation
Ozessa

We build and manage reliable data systems inside your Microsoft Fabric workspace. You own everything.

Corporate Entity

Ozessa is a trading name of OZESSA LTD.
Company No. 17120532 (England & Wales)

Registered Office:
167-169 Great Portland Street
5th Floor
London, W1W 5PF

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Insights
Management Standard
Securing Your Data Estate for AI Readiness
Owned by you. Built for truth.

Securing Your Data Estate for AI Readiness

Why you can't build AI on an un-governed lake.

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FABRICENGINE
ERP
CRM
API
SQL
IoT
XLS
DeploymentInside your Microsoft tenant
Data Ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft FabricEnterprise-grade architecture
Operational Depth
Executive Summary

AI models built on "dirty" data produce "Hallucinated" business rules.

Lack of data security leads to AI models leaking sensitive PII.

Unstructured data "swamps" are impossible for AI to navigate.

Read Time
15 MIN READ
Authority
Management Standard
Tier
Strategic Overview
KEY FACTS
FACT_01

80% of AI project failures are due to poor data quality.

FACT_02

Gating PII from AI models reduces legal risk by 95%.

FACT_03

Structured metadata increases AI model accuracy by 40%.

Definition

What is AI Readiness?

The state where a data estate is sufficiently clean, structured, and governed to support the safe and effective deployment of AI models.
Problem analysis
A. Symptom

Visible Signal

The AI gives different answers to the same question.

B. Business Impact

Consequence

Lack of trust in AI-driven automation.

C. Hidden Failure

Architecture Flaw

Treating AI as a "Magic Wand" for bad data.

Root cause

AI is a magnifying glass. If your data is 5% wrong, your AI will be 50% wrong. You cannot "out-AI" bad engineering. You must build the independent foundation first.

Our solution

The Reliability Engine Response

Our architecture mandates a reliability-first approach, injecting comprehensive markers and circuit breakers into the core transformation logic.

1

Implementing "Comprehensive Gating" for AI training sets.

2

Automated PII Masking for LLM integration.

3

Establishing a "High-Purity" Gold layer for AI consumption.

Business impact
Months of AI Rework
Time Recovered
$65,000+ (Project Waste)
Cost Mitigation
AI Hallucination
Risk Exposure
High-Purity
Metric Accuracy
Technical Analysis

Don't build AI on sand. Ozessa provides the bedrock foundation for AI Readiness. We ensure your data is ready for the future via Managed Data Reliability.

KEY TAKEAWAYS
  • ●Data is the fuel for AI; purity is the octane.
  • ●Ownership is required for safe AI deployment.
KEY DATA POINTS
Success Rate: 80% with Gated Data
Strategy: Comprehensive AI Integration
On this page
  • Executive Summary
  • Key Facts
  • Definition
  • Problem analysis
  • Root Cause
  • Our Solution
  • Business Impact
  • Technical Analysis
  • Key Takeaways
Share Record
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Why Data Reliability is the New Security

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Automating Regulatory Compliance in Fabric

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The Financial Risk of Logic Drift

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Need a forensic architecture audit?

We identify the manual cost and technical debt hidden in your current data estate.

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DATA ASSESSMENT

Request a data architecture review.

Stop relying on manual spreadsheets. Establish a reliable baseline and automate your reporting.

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Ready to fix your data?

Stop spending weekends reconciling spreadsheets. Let us build a reliable data system you own - inside your own Microsoft workspace.

DeploymentInside your Microsoft tenant
Data ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft Fabric
Enterprise-grade architecture
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