quality_assurance · saas · workflow
Google Cloud powers LLM evaluation service with Labelbox
Conducting large-scale, high-quality human evaluations of LLMs is a major challenge for enterprises, requiring significant time, resources, and expertise; human evaluation remains the gold standard for understanding nuances but is one of the most time-consuming and resource-intensive parts of the LLM development process.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Configure evaluation in Vertex AI
Vertex AI customers go directly into the Vertex AI interface to launch an LLM evaluation job and set their desired evaluation type and criteria.
Tools used
LabelboxVertex AIBigQuery · partnerCloudSQL · partnerGoogle Sheets · partner
Outcome
Customers can now develop and ship LLM applications with confidence, receiving high-quality results within days and launching evaluation jobs in minutes.
Results
Time savedwithin days
Grounding & classification
Source type: vendor customer story
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quality inspectionhuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedsoftwarecycle time reductiontime savedvendor customer storyquality assuranceai draft human approvalhuman review queue