AI Safety & Risk
AI Safety Assessment
FrontierScale AI assesses GenAI, LLM and agentic AI systems for safety, oversight, control effectiveness and deployment readiness before they reach production or scale.
Why this matters
GenAI and agentic AI introduce failure modes that traditional model risk frameworks were not designed for — prompt injection, jailbreaks, unsafe tool use, data leakage and autonomous decisioning. An AI safety assessment gives executives evidence that a system is safe to deploy, monitored in operation and controlled by design.
What we address
Problems this engagement solves
Model behaviour risk
Hallucinations, refusals and inconsistent outputs create customer and conduct exposure.
Prompt injection & jailbreaks
Systems can be manipulated through crafted inputs, retrieved content or tool outputs.
Data leakage
Sensitive data flows into prompts, embeddings, logs or third-party model APIs without control.
Unsafe tool use
Agentic systems execute actions with insufficient sandboxing, authorisation or oversight.
Weak human oversight
Escalation, review and override pathways are not designed for AI-assisted decisions.
Blind operation
Behaviour, drift and incidents are not monitored, logged or reported.
Our approach
How FrontierScale AI works
Step 01
System and threat scoping
Understand the AI system, data flows, model dependencies, tool use and threat model.
Step 02
Structured safety testing
Test behaviour, safety controls, prompt injection resilience, data handling and tool use.
Step 03
Oversight and control review
Assess human oversight, monitoring, escalation, incident response and audit trails.
Step 04
Deployment readiness decision
Produce a deployment readiness assessment with remediation, residual risk and executive summary.
Typical deliverables
Board-ready outputs
Every engagement produces evidence-backed artefacts your executives, auditors and regulators can review with confidence.
- AI safety assessment report
- Risk heatmap
- Control recommendations
- Testing plan and results
- Human oversight design
- Deployment readiness assessment
- Remediation roadmap
- Executive summary
Who it is for
Best-fit clients
- Chief AI Officers and product owners
- CROs and Heads of Model Risk
- CISOs and Heads of Cyber
- Compliance and Conduct Risk teams
- AI safety and platform engineering teams
Common triggers
When to engage
- Pre-production GenAI or agentic AI deployment
- Customer-facing AI or high-impact internal use
- Third-party AI or foundation model dependency review
- Post-incident or near-miss investigation
- Regulatory or investor readiness review
FAQs
Common questions
Do you do red-teaming?+
Yes — structured adversarial testing including prompt injection, jailbreak and unsafe tool use is a core part of most engagements, alongside control and oversight review.
Does this replace model validation?+
No. It complements model validation with GenAI- and agentic-specific safety, oversight and deployment concerns that traditional model risk frameworks do not fully cover.
How long does an assessment take?+
Typically 3–6 weeks depending on system complexity, integrations and level of adversarial testing required.
Related services
Explore related engagements
Make AI adoption defensible, governed and investment-ready
Speak with FrontierScale AI about AI governance, EU AI Act readiness, AI safety assessment or AI due diligence.