Call center ai · Production

Aloware converts 50% of client base to AI-powered packages with AssemblyAI

The problem

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.

Workflow diagram · grounded in source
1
Customer call received
trigger
“each call Aloware's customers receive could be transcribed automatically and at near human-level accuracy”
2
Speech-to-text transcription
ai_action
“Powered by AssemblyAI's industry-leading Universal model, this integration meant that each call Aloware's customers receive could be transcribed automatically and at near human-level accuracy”
3
Voice analytics processing
ai_action
“lets users check engagement time, review action items, generate speaker-separated transcripts, understand speaker sentiment, and define trackable keywords”
4
Call summary highlights
output
“Call Summary Highlights, which lets users tailor prompts and templates for customized summaries, leveraging AssemblyAI's automatic transcription and summarization models”
5
CRM sync from summaries
integration
“integrate into its customers' CRM, enabling seamless updates directly from call summaries into tools like Salesforce, HubSpot, and Zoho”
6
Continuous product improvement
feedback_loop
“Continuous updates to meet market demand and customer feedback”
Reported 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.

Reported metrics
client base converted to AI-powered packages50%
lead-to-close rate increase (JobNimbus)27%
Calls and texts processedmore than 200 million
AI transcription deployment timesix weeks
Reported stack
AssemblyAISpeech-to-Text APIUniversal modelLeMURAWSAWS BedrockSalesforceHubSpotZoho
Source
https://www.assemblyai.com/customers/aloware-customer-story
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

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.

What tools did this team use?

AssemblyAI, Speech-to-Text API, Universal model, LeMUR, AWS, AWS Bedrock, Salesforce, HubSpot, Zoho.

What results were reported?

client base converted to AI-powered packages: 50%; lead-to-close rate increase (JobNimbus): 27%; Calls and texts processed: more than 200 million; AI transcription deployment time: six weeks (source-reported, not independently verified).

How is this call center ai AI workflow structured?

Customer call received → Speech-to-text transcription → Voice analytics processing → Call summary highlights → CRM sync from summaries → Continuous product improvement.

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