Know Your GenAI Risk Profile Before You Ship

A 3-day structured diagnostic of your GenAI application - risk scorecard across 8 dimensions, prioritized remediation roadmap, and an executive summary ready for investors.

Duration: 3 days Team: 1 Senior GenAI QA Engineer

You might be experiencing...

You are shipping a GenAI product but have no systematic way to measure hallucination rates, accuracy, or safety posture.
Your Series B investors want AI safety documentation and you have nothing to show them.
You suspect your RAG system has retrieval quality issues but lack the evaluation framework to quantify them.
An enterprise prospect's procurement team asked for your AI QA process - and you don't have one.

The GenAI Readiness Assessment is the fastest way to understand your GenAI application’s quality risk - and the entry point for every genai.qa engagement.

What the Assessment Covers

Most GenAI teams have some form of testing. Few have a systematic view of their quality posture across all eight dimensions where GenAI applications fail in production:

Hallucination - Is your application generating factually incorrect or ungrounded output? We measure hallucination rates across representative user scenarios and categorize failure patterns.

Safety - Can adversarial users bypass your guardrails? We run targeted prompt injection and jailbreak probes to assess your safety boundary effectiveness.

Retrieval Quality - For RAG systems: is your retrieval pipeline returning the right context? We measure faithfulness, relevance, and grounding quality using industry-standard RAG evaluation metrics.

Coherence & Consistency - Does your application produce consistent outputs for semantically equivalent inputs? Inconsistency is the most common source of user trust erosion.

Latency - Are response times within acceptable thresholds for your use case? We benchmark p50, p95, and p99 latency under representative load.

Bias - Is your application producing outputs that systematically disadvantage specific user groups? We test for demographic and linguistic bias in output quality.

Security - Beyond prompt injection: system prompt exposure, data exfiltration via output, and information leakage through error messages.

Compliance - How does your current testing posture map to EU AI Act, NIST AI RMF, or industry-specific requirements? We identify the gaps before your auditor does.

Why Start Here

The Readiness Assessment gives you three things you cannot get from ad hoc testing:

  1. A risk scorecard - not a checklist, but a quantified assessment of actual risks in your specific application, ranked by severity and business impact.
  2. A remediation roadmap - the exact QA work that addresses your top risks, scoped and ready to execute.
  3. An executive summary - a 2-page document formatted for investors, board members, and enterprise procurement teams.

For teams preparing for Series B fundraising, enterprise customer procurement, or regulatory compliance review, the executive summary deliverable provides external validation documentation that internal testing cannot replace.

Book a free GenAI QA scope call to discuss whether a Readiness Assessment is the right starting point for your application.

Engagement Phases

Day 1

Architecture & Risk Mapping

Structured review of your GenAI application architecture: LLM selection, RAG pipeline, agent framework, prompt engineering approach, guardrails, and monitoring. We map every component against our 8-dimension risk matrix.

Day 2

Rapid Evaluation

Targeted testing across hallucination, safety, retrieval quality, coherence, latency, bias, security, and compliance dimensions. We run 50+ representative test cases to establish your baseline.

Day 3

Report & Remediation Roadmap

Delivery of a structured risk scorecard with prioritized remediation roadmap. Executive summary formatted for investor decks and board presentations.

Deliverables

Risk scorecard across 8 dimensions (hallucination, safety, retrieval, coherence, latency, bias, security, compliance)
Prioritized remediation roadmap (top 10 issues ranked by severity and business impact)
Executive summary (investor/board-ready, 2 pages)
Tool and framework recommendations for ongoing evaluation
30-minute debrief call to walk through findings

Before & After

MetricBeforeAfter
Time to First QA InsightNo formal GenAI QA process - unknown risk profileStructured risk scorecard delivered in 72 hours
Investor ReadinessNo AI safety documentation for due diligenceExecutive summary suitable for Series B technical due diligence
Cost vs. AlternativesBig Four assessment: $150,000+ and 3-6 monthsgenai.qa Readiness Assessment: $2,500 and 3 days

Tools We Use

Promptfoo DeepEval RAGAS OWASP LLM Top 10

Frequently Asked Questions

What access do you need?

We work from a structured intake questionnaire, architecture diagrams, and sample API access. We do not require source code, model weights, or production database access. Most teams complete intake in under 2 hours.

What is the price?

USD 2,500 for a 3-day assessment with full deliverables. Credit card checkout via Stripe, no MSA required. Below the $5,000 procurement threshold at most startups.

What happens after the assessment?

You receive a risk scorecard with sprint recommendations. No obligation to proceed. For teams that continue, the assessment fee is credited against the first sprint engagement.

How is this different from aiml.qa's Readiness Assessment?

aiml.qa tests models and data pipelines. genai.qa tests the application - user flows, prompt injection, RAG retrieval, agent safety, and end-to-end product quality. If your AI is a model, go to aiml.qa. If your AI is a product, start here.

Break It Before They Do.

Book a free 30-minute GenAI QA scope call. We review your AI application, identify the top risks, and show you exactly what to test before you ship.

Talk to an Expert