Trusted AI, independently evaluated.How We Objectively Evaluate AI Products
At huby, we evaluate AI products using a structured, data-driven framework designed to ensure consistency, transparency, and real-world relevance. This page is an overview of the process. The full methodology — scoring scale, source hierarchy, weighting and aggregation rules — is the authoritative reference and takes precedence where the two differ.
Our Evaluation Framework
Quality
- User experience and usability
- Output consistency and reliability
- Documentation and onboarding
- Testing and engineering quality
Use Cases & Pricing
- Breadth and depth of use cases
- Feature innovation
- Pricing transparency
- Value for money
Security
- Vulnerability and penetration testing
- API and infrastructure security
- Data protection (in transit and at rest)
- Access control mechanisms
Privacy
- Privacy policy transparency
- Compliance (GDPR, SOC2, HIPAA)
- Data handling practices
- User protection mechanisms
Sustainability And Reliability
- Company viability and funding
- Uptime, SLAs and incident history
- User base and growth
- Environmental impact
Impact, Ethics, And Safety
- Ethical AI policies
- Responsible AI usage
- Bias and fairness considerations
- Positive societal impact
Our Evaluation Process
Submission
Data Collection
Normalization
Evaluation
Scoring
Publication
1. Product Submission
Every evaluation starts with a submission, which can come from any of three routes: huby itself, which is how some products enter the queue and how every product in a category-wide comparative study is selected; a user who asks for a product to be evaluated; or a product owner submitting their own product. Regardless of route, the submission gathers:
- Product features and capabilities
- Pricing and licensing model
- Target users and use cases
- Technology stack and infrastructure
- Documentation and resources
2. Data Collection
We gather comprehensive data from multiple sources to build a complete product profile.
- Product research and testing by huby
- Official product documentation
- Public benchmarks and reviews
- Market and competitive landscape
- User expectations and feedback
3. Data Normalization
All data is standardized to ensure consistency across evaluations.
- Data cleaning and structuring
- Mapping to evaluation framework
- Removing inconsistencies
- Aligning comparable metrics
4. Evaluation
Products are assessed at a granular level across all framework dimensions.
- Factor-level analysis and scoring
- Subcategory and category level summaries
- Weighted aggregation scores at subcategory and category levels
- Review before publication
5. Reports
Structured insights and reports are generated for both internal and public use.
- Overall product rating/score
- Multi-level analysis and scoring
- Strengths and weaknesses
- Improvement recommendations
- Detailed and summary reports
6. Publication
Evaluated products are published and made discoverable on huby. Product owners who submit their own product control when their product is ready for evaluation, and separately enable publication, so that the product is not visible on huby before they have finished providing information. That control covers visibility only. Scores, assessments and evidence are determined by huby alone and are not shared with the owner for approval beforehand. For products huby submits itself, huby controls both steps and publishes regardless of the outcome.
- Submission enabled (by product owner, or by huby for its own submissions)
- Search indexing and discoverability
- Public availability
- Ongoing updates and re-evaluation
Evaluation Reports
Product Owner Report
- Detailed analysis down to the factor level
- Scoring breakdowns
- Actionable improvement feedback
Public Summary
- High-level evaluation insights
- Comparative positioning
- Final product score
Submit Your Product
Get objective evaluation, actionable insights, and visibility on huby — at no cost. Submitting does not influence product research or rating.
Submit Product