Measure reported readiness
Review your reported practices across acceptance criteria, regression testing, AI security, production monitoring, release evidence, RAG, and agents.
AI release readiness assessment
How ready is your AI system for production?
Score how exposed your system is, how strong your controls are, and how far the exposure runs ahead of the controls.
- 3 to 5 minutes
- 9 core questions
- Up to 4 conditional questions
- Personalized interpretation
What you receive
A scored readiness profile that explains what shaped the result
See what shaped the result
Connect the score to the lifecycle, users, data, architecture, and assurance practices selected in the assessment.
Prioritize technical validation
Receive focused validation priorities and questions to carry into release planning or a technical review.
What the assessment covers
GenAI applications, RAG systems, chatbots, and agentic workflows
The assessment scores the domains that apply to your system.
- Acceptance criteria
- Regression testing
- AI security
- Production monitoring
- RAG retrieval and grounding
- Agent permissions and actions
- Release evidence
Preparing your personalized result
Scoring your responses and generating a tailored interpretation
- Calculating exposure and maturity
- Connecting findings to selected answers
- Prioritizing validation areas
AI release readiness profile
Your AI release readiness assessment
Assurance maturity
0
Inherent exposure
0
Preliminary concern
0
These results are based on self-reported information. The personalized interpretation is generated from your responses. No technical testing or independent validation has been performed.
Priority area for technical validation
Reported assurance controls by domain
Higher values indicate more structured and repeatable reported practices.
How your answers shaped the result
Personalized findings
Potential gaps
Business implications
Positive reported practices
Recommended validation focus
Priorities based on your response pattern
A TestSavant.AI specialist can help determine which areas warrant technical validation against the real application, data, models, retrieval sources, tools, and workflows.
Questions to carry into a technical review
Use these questions to clarify scope, evidence, and release confidence with engineering, QA, security, and AI product stakeholders.
How this score was calculated
Inherent exposure uses lifecycle, user reach, data sensitivity, architecture, external access, production status, and high-impact agent actions where applicable.
Assurance maturity uses reported acceptance criteria, regression testing, AI security, production monitoring, release evidence, plus the RAG and agent domains where applicable.
Preliminary concern is calculated as 65% of inherent exposure plus 35% of the inverse of assurance maturity.
