Buyer problem
Models can appear fluent while producing incorrect morphology, unnatural register, mixed-direction formatting errors, unsupported claims, weak refusals, or inconsistent behavior across semantically equivalent prompts.
Suitable use cases
- Hebrew chatbot and assistant evaluation
- Pre-release model comparison
- Regression testing after prompt or model changes
- Domain-specific factuality and terminology review
- Safety, refusal, and instruction-compliance testing
Inputs required from the client
- Model access or exported outputs
- Target use cases and user groups
- Policies, expected behavior, and severity definitions
- Domains and terminology that require specialist review
- Desired scoring scale and reporting format
Evaluation dimensions
- Native Hebrew fluency
- Morphology and agreement
- Hebrew-English code-switching
- Right-to-left formatting
- Domain terminology
- Instruction following
- Factuality and unsupported claims
- Safety and policy compliance
- Tone and cultural appropriateness
- Consistency across prompt variants
Method and workflow
A pilot rubric and test set are created from the intended use cases. Outputs are evaluated, errors are assigned to a defined taxonomy, severe failures are escalated, and the rubric is revised before a larger evaluation run.
Deliverables
- Evaluation rubric
- Test-case set
- Annotated model outputs
- Error taxonomy
- Quantitative score summary
- High-severity failure examples
- Remediation recommendations
Acceptance criteria and quality metrics
Metrics may include pass rate, severity-weighted failure rate, consistency across variants, factuality rate, refusal quality, language-quality score, and reviewer agreement.
Example output
Review the sample Hebrew LLM evaluation report and sample model failure taxonomy.
Data-handling considerations
Evaluation can use non-confidential prompt sets, exported model outputs, or secure client-controlled environments. Sensitive production data is not requested through the public form.
Request a Hebrew LLM evaluation pilot
A pilot typically covers a defined use case, a small test-case set, an agreed rubric, annotated outputs, and an initial failure analysis.