What We Do

Responsible AI Assessments

Most organisations that have deployed AI have done so faster than their governance frameworks evolved. We close that gap — with a structured, evidence-based assessment that gives leadership a clear picture of where they stand, and what to do about it.

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Risks we assess

Regulatory non-compliance
EU AI Act, ISO 42001, NIST AI RMF
Fairness & bias failures
Disparate outcomes across groups
Data privacy violations
PII leakage in training data or prompts
Model drift & degradation
Silent performance decay post-deployment
Lack of human oversight
Autonomous systems without escalation paths
Opaque decision-making
AI outputs with no explainability trail

Five domains. One clear picture.

Aligned to the EU AI Act, ISO 42001, and the NIST AI Risk Management Framework.

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01

AI Inventory & Classification

Complete register of every AI system in use — including shadow AI — classified by risk level.

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02

Fairness & Bias Review

Analysis of training data and model outputs for evidence of disparate impact.

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03

Data & Privacy Compliance

Review of data handling across the AI pipeline against applicable privacy frameworks.

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04

Human Oversight Architecture

Assessment of human-in-the-loop positions, escalation paths, and override mechanisms.

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05

Governance & Policy Maturity

Evaluation of AI policies, accountability structures, and regulatory readiness.

What you receive

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Executive Summary

A board-ready summary of your AI risk posture — what you have, what the risks are, and what actions are most urgent.

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Detailed Findings Report

Comprehensive review of all findings and evidence gathered from across your AI systems.

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Prioritised Remediation Roadmap

Ranked list of recommended actions with effort estimates, ordered by risk severity and business impact.

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Governance Framework

Practical policies, processes, and tooling recommendations to sustain responsible AI at scale.

Know where you stand.

Book an initial call to scope a Responsible AI Assessment for your organisation.

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