back_office_ops · saas · workflow
Grain increased customer satisfaction by 12% after integrating AssemblyAI
Grain needed the highest possible transcription accuracy to generate intelligent insights for its customers, which led the product team to switch from their previous provider, Rev, to AssemblyAI.
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 · Conversation captured as data
Every conversation—from phone calls to lectures to team meetings—is treated as data that can be put in a digital format and manipulated by LLMs.
Tools used
AssemblyAILLMsAutomatic Language Detection (ALD)
Outcome
After integrating AssemblyAI's Voice AI models, Grain saw customer satisfaction increase by 12%, and the platform can now accurately serve its highly international customer base in core languages.
What failed first
Grain's previous transcription provider, Rev, did not deliver the accuracy level required to power high-quality AI insights.
Results
Volume12%
Grounding & classification
Source type: vendor customer story
22 fields verified against source quotes.
data extractionspeech to textsummarizationcall recordingmeeting recordingmetric backednamed customerproduction runtime claimedsource backedtools describedvendor confirmedworkflow describedsoftwareaccuracy improvementcustomer satisfactionemployee productivityvendor customer storyback office opsmeeting to artifacts