Eval directory
Evals for Granola
7 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Granola AI products.
About Granola
Granola is an AI notepad for meetings that runs locally on macOS, capturing audio from any meeting tool and generating structured, editable notes with action items and summaries — without bots or calendar integrations.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
7/7 packs
Scoring metrics
0/7 packs
Judge rubrics
7/7 packs
Use-case maps
0/7 packs
Pack context
7/7 packs
Available eval packs for Granola
7 packs ready to run.
Chat And Meeting Library Grounding
Answer RelevanceEvaluates Granola's Granola Chat & Meeting Library Grounding across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Integration Write Safety
Evaluates Granola's Integration Write Safety across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Native Capture And Recording Consent
Evaluates Granola's Native Capture & Recording Consent across 8 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Pii Redaction And Compliance Controls
PII LeakageEvaluates Granola's PII Redaction & Compliance Controls across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Template Driven Notes And Ai Enhancement
Evaluates Granola's Template-driven Notes & AI Enhancement across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Transcription Asr And Speaker Attribution
Transcription AccuracyEvaluates Granola's Transcription ASR & Speaker Attribution across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Workspace Permissions Search And Retention
Evaluates Granola's Workspace Permissions, Search & Retention across 8 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
Why eval Granola AI
Granola's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Granola measures four dimensions teams care about most when deploying productivity ai agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Granola's public product surface and runnable in Corsac with your own data.