This 2-minute assessment provides instant recommendations for evaluation approaches based on your project characteristics. Answer the questions below to get customized guidance on metrics, tools, and implementation priorities.
What best describes your AI system?
- A) High-Stakes Application (Medical, Legal, Financial, Safety-Critical)
- Score: 10 points
- Risk Level: Critical
- B) Business-Critical Application (Customer-facing, Revenue-impacting)
- Score: 7 points
- Risk Level: High
- C) Internal Tool (Employee productivity, Process automation)
- Score: 4 points
- Risk Level: Medium
- D) Experimental/Prototype (Research, Testing, MVP)
- Score: 2 points
- Risk Level: Low
What's your expected usage volume?
- A) Enterprise Scale (>100K interactions/day)
- Score: 8 points
- Scale: Very High
- B) High Volume (10K-100K interactions/day)
- Score: 6 points
- Scale: High
- C) Medium Volume (1K-10K interactions/day)
- Score: 4 points
- Scale: Medium
- D) Low Volume (<1K interactions/day)
- Score: 2 points
- Scale: Low
How critical is output quality?
- A) Perfect Quality Required (Zero tolerance for errors)
- Score: 10 points
- Quality: Critical
- B) High Quality Expected (Occasional minor errors acceptable)
- Score: 7 points
- Quality: High
- C) Good Quality Sufficient (Some errors acceptable if caught)
- Score: 4 points
- Quality: Medium
- D) Basic Quality Acceptable (Errors can be corrected post-generation)
- Score: 2 points
- Quality: Basic
What evaluation resources do you have?
- A) Dedicated Team (Full-time evaluation specialists)
- Score: 8 points
- Resources: High
- B) Part-time Expertise (Team members with evaluation knowledge)
- Score: 6 points
- Resources: Medium-High
- C) Limited Expertise (Some technical knowledge available)
- Score: 4 points
- Resources: Medium
- D) Minimal Resources (Learning as you go)
- Score: 2 points
- Resources: Low
When do you need to launch?
- A) Already in Production (Need evaluation now)
- Score: 8 points
- Urgency: Critical
- B) Launching Soon (<4 weeks)
- Score: 6 points
- Urgency: High
- C) Planning Phase (1-3 months)
- Score: 4 points
- Urgency: Medium
- D) Early Development (3+ months)
- Score: 2 points
- Urgency: Low
Add up points from all 5 questions: _ / 44 points
- Evaluation Mix: 60% Human Expert + 30% LLM-as-Judge + 10% Automated
- Implementation Timeline: Start immediately, full deployment in 2-4 weeks
- Budget Allocation: $2000-5000/month
- Team Requirements: Dedicated evaluation specialist + domain experts
- Safety Implementation: Deploy comprehensive safety checks immediately
- Expert Review Setup: Establish human evaluation protocols
- Monitoring Dashboard: Create real-time quality monitoring
- Escalation Procedures: Define clear escalation paths for failures
- Safety compliance: >99%
- Expert accuracy review: >95%
- Response time monitoring: <2 seconds
- User satisfaction tracking: >4.5/5.0
See Tool Comparison Matrix for detailed selection guidance:
- Professional human evaluation: Scale AI, Labelbox
- Enterprise LLM APIs: GPT-4, Claude-3 Opus
- Real-time monitoring: DataDog, Prometheus
- A/B testing framework
- Evaluation Mix: 35% Human Review + 45% LLM-as-Judge + 20% Automated
- Implementation Timeline: 2-4 weeks for full deployment
- Budget Allocation: $500-2000/month
- Team Requirements: Part-time evaluation focus + technical team
- Core Metrics: Implement Big 3 safety metrics (safety, relevance, coherence)
- LLM-as-Judge: Deploy automated quality assessment
- User Feedback: Set up feedback collection system
- Basic Monitoring: Create quality dashboard
- Safety rate: >95%
- Relevance score: >80%
- User satisfaction: >4.0/5.0
- System uptime: >99%
See Tool Comparison Matrix for detailed selection guidance:
- LLM evaluation APIs: OpenAI, Anthropic
- Open-source safety models: HuggingFace
- Analytics platform: Mixpanel, Amplitude
- Basic A/B testing
- Evaluation Mix: 20% Human Sampling + 50% LLM-as-Judge + 30% Automated
- Implementation Timeline: 1-2 weeks for initial deployment
- Budget Allocation: $200-500/month
- Team Requirements: Technical team with part-time evaluation focus
- Safety First: Basic safety and toxicity detection
- Automated Quality: LLM-based relevance and coherence checking
- User Metrics: Simple feedback collection
- Performance Monitoring: Response time and error tracking
- Safety compliance: >90%
- Automated quality score: >75%
- User feedback rating: >3.5/5.0
- Response time: <3 seconds
- Open-source evaluation frameworks (RAGAS, LangChain)
- Cost-effective LLM APIs (GPT-3.5, Claude-3 Haiku)
- Simple analytics (Google Analytics, Posthog)
- Basic monitoring tools
- Evaluation Mix: 10% Human Spot-Check + 30% LLM-as-Judge + 60% Automated
- Implementation Timeline: 2-5 days for basic implementation
- Budget Allocation: $50-200/month
- Team Requirements: Development team with basic evaluation knowledge
- Basic Safety: Simple toxicity detection
- Length/Format Validation: Automated checks for obvious failures
- Simple Relevance: Semantic similarity scoring
- Basic Logging: Track all interactions for future analysis
- Safety check: >85%
- Format compliance: >95%
- Basic relevance: >70%
- System stability: >95%
- Free/open-source tools (HuggingFace transformers)
- Basic semantic similarity models
- Simple logging (Python logging, file storage)
- Minimal monitoring setup
- Implement safety/toxicity detection
- Set up basic logging for all AI interactions
- Create simple monitoring dashboard
- Define success criteria for your use case
- Test evaluation system with sample data
- Achieve target metrics for your score range
- Collect baseline performance data
- Identify top 3 improvement opportunities
- Plan next phase of evaluation enhancement
- Consistent metric achievement for 2+ weeks
- User satisfaction trend (if applicable)
- System reliability >95%
- Clear ROI from evaluation investment
When to Retake This Assessment:
- After major system changes or feature additions
- When scaling to significantly higher volume
- After 3-6 months of operation
- When changing business requirements or use cases
- After collecting substantial user feedback data
Based on your assessment score:
- High Scores (30+): Move to Master Implementation Roadmap for enterprise planning
- Medium Scores (15-29): Continue with Evaluation Selection Wizard for detailed guidance
- Low Scores (5-14): Start with Starter Evaluation Toolkit for day 1 implementation
- Any Score: Use Cost-Benefit Calculator to justify your evaluation investment
- Evaluation Selection Wizard: Interactive guidance for detailed metric selection
- Starter Evaluation Toolkit: Day 1 implementation with code examples
- Master Implementation Roadmap: Long-term strategic planning
- Cost-Benefit Calculator: ROI analysis and budget planning
- Decision Trees: Task-specific metric selection (Primary Authority)
- Tool Comparison Matrix: Vendor and platform selection (Definitive Source)
- Quality Dimensions: Comprehensive metric definitions
- Implementation Guides: Technical setup instructions
This quick assessment provides immediate direction while the detailed framework materials offer comprehensive implementation guidance.