Measuring trust through quality

At Graph, we believe trust must be earned through measurable, verifiable quality standards. We've embedded this philosophy directly into our product development process, creating a public Quality Dashboard that holds us accountable to the high standards engineering teams deserve.Our proprietary quality evaluator system evaluates every interaction with Graph across four critical dimensions:

  • Completeness: How thoroughly responses leverage available data sources, demonstrate understanding of engineering dynamics, identify specific patterns, and provide actionable insights -- not just observations.
  • Clarity: Technical accuracy is paramount. Responses must be immediately comprehensible to engineers, explicitly state data sources and methodologies, and distinguish clearly between facts and inferences.
  • Formatting: Strategic use of markdown, tables, and emphasis to enhance technical readability and highlight key metrics and trends.
  • Conciseness: Every response leads with key insights, eliminates fluff, and adheres to the Minto principle - summarize first, then present supporting data. We reject AI platitudes in favor of concrete, actionable guidance.

Each dimension is scored on a rigorous 0.0-1.0 scale, where 1.0 represents exceptional performance with profound, unique insights. Anything below 0.5 indicates gaps in technical understanding or accuracy. We maintain this strict scoring system because we understand that in engineering, inconsistent or hallucinated outputs aren't just annoying - they're destructive to productivity and trust. The Quality Dashboard gives you complete visibility into how we're measuring up to these standards.