Patented AI Assurance Technology
Published international and U.S. patent applications covering autonomous AI red teaming and compliance-enforcement technology.
AI Evaluating AI • Independent Assurance • Continuous Validation
AI Evaluating AI.
Independent Continuous AI Assurance
Independent Continuous AI Assurance for AI systems, LLM applications, RAG platforms and agentic AI. We help organisations validate AI before deployment, continuously in production, and after significant model, prompt, tool or agent changes.
Continuous AI Assurance
AI Red Teaming
LLM & Agentic AI Assurance
Independent AI Assurance
Assessment Scope
AI Assurance Assessment
Deployment readiness, governance gaps, risk findings
Custom Scope
AI Red Teaming
Adversarial scenarios, failure modes, robustness gaps
Custom
LLM & Agentic AI Assurance
Prompt injection, data leakage, tool misuse, workflow risk
Custom
Continuous AI Assurance
Ongoing validation, re-assurance and executive reporting
Retainer
AI Assurance Framework (AIAF)
A published, evidence-based methodology for Independent and Continuous AI Assurance across governance, technical evaluation, reporting and re-assurance.
Independent Assessment
Objective evaluation separate from model developers, implementation teams and vendors.
Evidence-Based Reporting
Findings translated into executive, risk, regulatory-readiness and assurance evidence.
AI systems evolve. Assurance should too.
Traditional security testing was designed for software. Modern AI systems introduce new categories of risk including hallucinations, prompt injection, unsafe outputs, model misuse, data leakage, tool misuse, model drift, prompt changes and unpredictable autonomous behaviour.
Continuous assurance, guided by human experts.
AegisRT combines independent expert assessment with proprietary autonomous testing methodologies to evaluate whether AI systems continue to operate safely, reliably and within approved expectations. Technology supports the assessment; expert judgement interprets the risk.
The Continuous AI Assurance lifecycle.
AI Governance defines expectations. Continuous AI Assurance provides ongoing evidence that AI systems continue to operate within those expectations as models, prompts, tools, agents and risks evolve.
Initial Assurance
Assess AI systems before deployment to identify safety, reliability, security and governance-readiness gaps.
Production Assurance
Continue validating AI systems after deployment through periodic testing and evidence-based reporting.
Change Assurance
Re-assure AI systems after significant model, prompt, RAG, tool, workflow or agent changes.
Enterprise Trust
Provide assurance evidence for executives, risk teams, governance functions, customers and regulators.
Service packages designed for real AI lifecycle risk.
Engagements are scoped based on model type, deployment stage, production risk, testing coverage, governance requirements and reporting needs.
AI Assurance Assessment
Custom Scoped Engagement
Independent review of AI systems, models and workflows to identify risks affecting reliability, safety, governance readiness and deployment confidence.
- Executive summary
- Risk findings and scoring
- Governance observations
- Assurance recommendations
Continuous AI Assurance
Retainer / Periodic Review
Ongoing assurance for AI systems after deployment, including re-assurance following significant model, prompt, tool, RAG or agent changes.
- Periodic validation
- Change-triggered re-assurance
- Trend and risk reporting
- Executive assurance evidence
AI Red Teaming Engagement
Custom Scoped Engagement
Structured adversarial testing designed to identify AI-specific failure modes, behavioural weaknesses, robustness gaps and security issues under realistic attack scenarios.
- Adversarial scenario testing
- Failure mode analysis
- Robustness assessment
- Technical and executive reporting
LLM & Agentic AI Assurance
Custom Scoped Engagement
Assessment of LLM applications, RAG platforms, copilots and agentic workflows interacting with tools, data, APIs and automated actions.
- Prompt injection testing
- Data leakage assessment
- Tool misuse analysis
- Agent workflow evaluation
What makes AegisRT different.
AegisRT is positioned between pure consulting and pure software scanning: independent Continuous AI Assurance supported by expert assessment and proprietary autonomous testing technology.
Independent Assessment
Objective evaluation separate from model developers, implementation teams and vendors.
Published Assurance Methodology
Assessments are guided by the AI Assurance Framework (AIAF), supported by proprietary autonomous testing technology for AI-specific failure modes, behavioural weaknesses and robustness gaps.
Assurance-Oriented Reporting
Findings are translated into practical evidence for management, compliance, risk, oversight and regulatory-readiness functions.
Human + Autonomous Evaluation
Expert judgement is combined with systematic testing to improve assessment coverage, repeatability and interpretation.
Technology operationalising the assurance methodology.
AegisRT operationalises AIAF through proprietary autonomous testing capabilities incorporating adaptive adversarial generation, autonomous scenario exploration, behavioural robustness evaluation, re-assurance and evidence-based reporting workflows.
- Adaptive adversarial evaluation
- Autonomous scenario exploration
- Behavioural robustness assessment
- Assurance, re-assurance and reporting workflows
Technology supported by published patent applications.
AegisRT assessments are supported by proprietary technology covered by published international and U.S. patent applications relating to autonomous AI red teaming and compliance enforcement using adversarial machine learning.
- WO2026/105011
- US20260141256A1
- View WIPO publication
The technology supports assessment outcomes and does not replace expert review.
AegisRT ecosystem.
Beyond assurance engagements, AegisRT develops practical AI security and governance-support tools to support responsible AI adoption.
AegisRT Shield
Browser-based prompt protection and sensitive information masking for AI assistants and copilots.
- Local masking and restoration workflow
- Protection of client and organisational information
- Useful for AI governance and safe prompt workflows
AegisRT Platform
Internal assurance delivery platform supporting AI evaluation, adversarial testing and structured reporting workflows.
- Evaluation management
- Risk reporting workflow
- Model and endpoint assessment roadmap
Future Continuous Assurance Modules
Additional continuous assurance and assessment capabilities are planned for LLM applications, RAG systems and agentic workflows.
- Endpoint assessment
- Agent workflow testing
- Continuous AI Assurance reporting
Built for organisations deploying and operating AI in real workflows.
AegisRT supports organisations across the AI lifecycle: initial assurance before deployment, continuous assurance in production, and re-assurance after significant model, prompt, tool or agent changes.
Financial Services
AI governance, model assurance, internal copilots, customer-facing bots and workflow automation.
Government & Public Sector
Independent assurance for AI systems used in operational, citizen service and decision-support environments.
Enterprise AI Teams
Assurance for LLM applications, RAG systems, knowledge assistants and internal automation tools.
AI Product Vendors
Independent testing and assurance reports to support enterprise adoption and deployment confidence.
How an assessment works.
A practical workflow for organisations that need independent AI assurance before deployment and continuous confidence after AI systems enter production.
Scope
Define the AI system, use case, deployment context, risks and assurance objectives.
Evaluate
Conduct expert-led testing supported by proprietary autonomous evaluation methodologies.
Report
Deliver risk findings, assurance observations, executive summary and recommended next steps.
Re-Assure
Support remediation planning, retesting and a Continuous AI Assurance roadmap where required.
Request an assessment scope.
Share your AI use case and we will follow up to scope the appropriate assessment. Suitable for AI models, LLM applications, RAG systems, copilots and agentic workflows before deployment, in production or after significant changes.