AI Tool Evaluation
& Vendor Due Diligence
Know what works. Know what breaks.
Before it's too late.
We independently evaluate AI tools and vendors under real-world conditions — not controlled demos. One question drives everything: Will this system actually work safely, reliably, and compliantly in your environment?
The cost of skipping due diligence
The evidence base for AI deployment failures is growing. These are not edge cases.
76%
of AI projects fail to meet their intended objectives
Gartner, 2024 — citing misalignment between vendor claims and production performance as a primary cause.
$5.5M
average cost of a single AI-related data breach
IBM Cost of a Data Breach Report, 2024 — incidents involving AI systems now exceed the global average.
60%
of organisations conduct no adversarial testing before AI deployment
KPMG AI in Control Survey, 2024 — most rely solely on vendor-supplied benchmarks and documentation.
€35M
maximum fine for high-risk AI Act violations per incident
EU AI Act, 2024 — organisations deploying unvalidated high-risk AI systems face direct regulatory liability.
Sources: Gartner AI Deployment Report 2024 · IBM Cost of a Data Breach 2024 · KPMG AI in Control Survey 2024 · EU Artificial Intelligence Act (Regulation (EU) 2024/1689)
Most organisations are flying blind
on AI decisions
Procurement decisions are driven by vendor demos, benchmarks that don't reflect real usage, and internal enthusiasm rather than evidence.
In regulated environments — finance, healthcare, legal — the gap between what vendors promise and what systems deliver in production carries direct regulatory, reputational, and operational exposure.
The consequences of skipping due diligence
Tools that don't scale
Performance degrades under real data volume and concurrent usage.
Hidden production risks
Edge cases invisible in demos surface only in live systems.
Regulatory exposure
EU AI Act, GDPR and sector regulations carry significant penalties for non-compliant deployments.
Loss of stakeholder trust
System failures erode confidence in AI programmes across the organisation.
Wasted time and budget
Ripping out embedded AI tools post-deployment costs far more than pre-deployment evaluation.
Our Evaluation Framework
Six dimensions. Structured methodology. Delivered in 3–10 days.
Real-World Performance Testing
Test against your actual use cases and data
Accuracy, consistency, and edge-case handling
Identify where outputs degrade or fail
Adversarial & Safety Testing
Prompt injection and jailbreak testing
Data leakage and hallucination analysis
Agent and tool misuse scenarios
AI Controls & Guardrails Assessment
Output validation mechanisms
Human-in-the-loop controls
Monitoring and fallback logic
Compliance & Regulatory Alignment
GDPR and data handling risks
EU AI Act, NIST AI RMF, ISO 42001 alignment
Auditability and traceability requirements
Architecture & Integration Review
API reliability and latency under load
Workflow fit within your existing systems
Scalability and cost under load
Vendor Risk & Maturity Assessment
Model transparency and stated limitations
Security posture and data usage policies
Long-term viability and dependency risk
What you receive
Every evaluation concludes with a structured set of outputs designed to support decision-making at board, risk, and engineering levels.
Go / No-Go / Conditional Recommendation
A clear, defensible deployment decision — not a hedged summary.
Risk Heatmap
Where the system fails, under what conditions, and severity of exposure.
Mitigation & Remediation Plan
Specific steps to make the system safe and production-ready.
Vendor Comparison Report (if applicable)
Side-by-side evaluation across competing platforms.
Executive-Ready Board Summary
C-suite briefing document for confident, informed decision-making.
When organisations call us
We work across industries where failure carries real consequences.
Selecting between multiple AI vendors
Objective, evidence-based comparison before committing budget.
Validating before enterprise rollout
Confirm production-readiness before organisation-wide deployment.
Regulated industry deployments
Finance, healthcare, legal, and public sector AI with compliance obligations.
Stress-testing agentic workflows
Autonomous AI agents need adversarial testing before live deployment.
Procurement & risk team support
Independent technical assurance to complement legal and commercial due diligence.
How we work
Rapid evaluation cycles delivered in secure, isolated environments with close collaboration across your teams.
Intake & Scoping
Define objectives, data access, and evaluation environment.
Structured Testing
6-dimension evaluation in secure, isolated environment.
Risk & Gap Analysis
Findings mapped to risk severity, compliance gaps, and failure modes.
Report & Debrief
Structured outputs and executive summary delivered with debrief.
Why clients choose T3
We work exclusively with organisations where failure is not an option. Our team combines AI engineering depth, adversarial testing methodology, and regulatory expertise — a combination most consultancies cannot replicate.
AI Engineering + Adversarial Testing
Deep technical AI expertise combined with structured adversarial methodology.
Regulatory Expertise
Direct practitioner experience across EU AI Act, GDPR, ISO 42001 and NIST RMF.
Contributed to Global AI Standards
We help shape the standards your vendors are evaluated against.
Before you commit to an AI vendor,
make sure it survives reality.
Our evaluations are rapid, thorough, and actionable. Speak to our team to discuss your use case and receive a scoping proposal within 24 hours.
