What is PromptReports.AI?

PromptReports.AI is an AI-powered platform that creates professional executive research reports in minutes. It provides market analysis, financial reports, and strategic intelligence customized for your business needs.

How does AI report generation work?

Our platform uses advanced AI models to analyze your input data and generate comprehensive research reports. Simply provide your topic or data, select a report template, and our AI creates a professional document with insights, analysis, and recommendations.

What types of reports can I create?

You can create market analysis reports, competitive intelligence reports, trend scanning reports, financial analysis, strategic assessments, and custom research reports tailored to your specific industry or topic.

Yes, we prioritize data security. All data is encrypted in transit and at rest. We do not share your data with third parties, and you maintain full ownership of all reports generated on our platform.

Evaluation & Testing Overview

Ensure prompt quality with comprehensive testing: batch evaluations, A/B tests, pairwise comparisons, backtesting, and regression testing.

Why Evaluate Prompts?#

Prompt quality directly impacts user experience, business outcomes, and operational costs. Without systematic evaluation, you're flying blind—unable to know if changes improve or degrade performance, or how your prompts handle edge cases.

Professional prompt evaluation provides:

Quality Assurance

Verify prompts work correctly across diverse inputs before deployment.

Performance Tracking

Monitor quality metrics over time and catch degradation early.

Objective Comparison

Compare prompt versions with statistical rigor, not just intuition.

Risk Mitigation

Prevent quality regressions from reaching production users.

For AI Experts

PromptReports evaluation tools are designed for professional workflows. You can:

Define custom scoring criteria beyond basic metrics
Run statistically significant A/B tests
Automate regression testing in CI/CD pipelines
Export results for further analysis in your preferred tools

Evaluation Types#

PromptReports supports multiple evaluation methodologies for different use cases:

Type	Purpose	Best For
Batch Evaluation	Run prompt against all test cases and measure quality	Regular quality checks, pre-deployment validation
A/B Testing	Compare two versions with random assignment and statistical analysis	Deciding between competing prompt versions
Pairwise Comparison	Head-to-head evaluation on identical inputs	Detailed quality analysis, preference ranking
Backtesting	Run new version against historical execution data	Understanding impact before deployment
Regression Testing	Compare against production baseline before promotion	Preventing quality degradation in releases

Batch Evaluation

Run your prompt against every row in a test dataset and collect results.

A/B Testing

Split traffic between versions and measure statistical significance.

Pairwise Comparison

Compare two versions side-by-side on the same inputs.

Backtesting

Test against historical data before deploying changes.

Test Datasets#

Test datasets are the foundation of systematic evaluation. A good dataset includes:

Representative Inputs

Cover the range of inputs your prompt will encounter in production.

Edge Cases

Include challenging inputs that might cause failures or unexpected behavior.

Expected Outputs (Optional)

For automated scoring, include reference outputs to compare against.

Metadata

Add tags or categories to enable filtered analysis.

Example Dataset (CSV)

csv

input_text,expected_tone,category
"I'm frustrated with my order","empathetic",complaint
"What are your business hours?","informative",inquiry
"This is the third time I've called!","apologetic",escalation
"Thanks for your help!","appreciative",positive

Test datasets can be created manually, imported from CSV files, or generated from execution history. Use representative inputs covering normal cases, edge cases, and potential failure modes.

Quality Metrics#

PromptReports tracks several quality metrics to help you understand prompt performance:

Metric	Description	Range
Relevance	How well the response addresses the input	1-5
Coherence	Logical flow and clarity of the response	1-5
Completeness	Whether all aspects of the task were addressed	1-5
Accuracy	Factual correctness (when reference available)	1-5
Tone Match	Alignment with expected tone/style	1-5
Overall Quality	Aggregate score across all metrics	1-5

Custom Metrics

For specialized use cases, you can define custom evaluation criteria. This is particularly useful when standard metrics don't capture what matters for your domain.

Workflow Integration#

Evaluation integrates seamlessly into your prompt development workflow:

Development

Run evaluations frequently during development to validate changes.

Pre-Promotion

Run comprehensive evaluation before requesting promotion to staging.

Regression Gate

Automatic regression testing blocks promotions if quality drops.

Production Monitoring

Schedule periodic evaluations to detect drift over time.

The regression testing feature automatically compares your new version against the current production version. If quality drops more than 5%, promotion is blocked. This ensures changes never degrade production quality.

Getting Started#

Ready to start evaluating? Follow these steps:

1. Create a Dataset

Build a test dataset with representative inputs.

2. Run Evaluation

Execute your prompt against the dataset.

3. Analyze Results

Review quality metrics and individual responses.

4. Set Up Regression

Configure automatic regression testing.

PreviousVersion Control

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