call_center_ai · saas · workflow
Aloware converts 50% of client base to AI-powered packages with AssemblyAI
Aloware needed a fast, scalable voice AI foundation to ship AI-powered features — including call transcription, sentiment analysis, and summarization — to its contact center customers without building costly internal AI infrastructure.
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 · Customer call received
Each call Aloware's customers receive triggers automatic transcription.
Tools used
AssemblyAISpeech-to-Text APIUniversal modelLeMURAWSAWS Bedrock
Outcome
Since launching AloAi Voice Analytics in December 2024, 50% of Aloware's client base converted to AI-powered packages, and customers like JobNimbus achieved a 27% increase in lead-to-close rate.
Results
Time savedsix weeks
Volume50%
Running sinceDecember 2024
Grounding & classification
Source type: vendor customer story
31 fields verified against source quotes.
data extractionsentiment analysisspeech to textsummarizationcall recordingmetric backednamed customerproduction runtime claimedtools describedworkflow describedsoftwareautomation rateconversion increasetime savedvendor customer storycall center aiquality assurancesales opsdata sync enrichmentvoice call handling