Aloware
Aloware’s bet on AI pays off: After integrating AssemblyAI’s leading Speech AI models, the company converts 50% of its client base to its popular AI-powered packages.
of client base converted to AI-powered packages
increase in lead-to-close rate
million calls and texts processed
The evolution of contact centers
Aloware is an AI-powered contact center solution that specializes in helping companies turn more leads into deals for companies worldwide. Since its inception in 2018, the contact center world has shifted significantly, says Hugo Salomon, Senior Product Manager at Aloware.
This includes using AI for:
Automating repetitive tasks like summarizing calls or scheduling an appointmentAnalyzing customer sentiment to generate personalized resolutionsCreating AI agents that can facilitate high-value client interactionsToday, Aloware has processed more than 200 million calls and texts worldwide while continuing to expand and innovate with AI to drive further growth—all powered by its robust AWS infrastructure.
Deploying AI transcription in just six weeks
As a first step to deploying AI-powered applications, Aloware integrated AssemblyAI's Speech-to-Text API, shipping its AI transcription feature to its customers in just six weeks. 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. This rapid deployment was possible due to both companies' strategic decision to build their services on AWS, enabling seamless integration and exceptional performance at scale.
Now, tedious tasks like QA and call reviews can be expedited while simultaneously reducing the potential for human error, significantly increasing both the accuracy and utility of the analysis.
Sohrab Sheikhani, founder of Aloware, explains why they chose to partner with AssemblyAI:
Aloware also liked that these Speech AI models came from a single provider, condensing their AI stack and making its smart tools easier and faster to build and deliver to its customers.
In addition, Sheikhani explains that AssemblyAI's demonstrated commitment to continuous model and feature improvement through its in-house AI research was a big deciding factor.
Building AloAi Voice Analytics
After conducting customer research, Aloware decided to launch AloAi Voice Analytics, a new AI-powered analytics tool built on AWS that lets users check engagement time, review action items, generate speaker-separated transcripts, understand speaker sentiment, and define trackable keywords.
AloAi Voice Analytics also includes Call Summary Highlights, which lets users tailor prompts and templates for customized summaries, leveraging AssemblyAI's automatic transcription and summarization models.
Since its launch in December 2024, Aloware has seen 50% of its client base convert to its suite of AI-powered packages, with AWS providing the scalable foundation to support this rapid growth.
Salomon continues: "Utilizing AssemblyAI's features allowed Aloware to quickly scale and improve AloAi Voice Analytics without dedicating extensive internal development resources."
Key features driving customer success
Key features of AloAi include:
Automatic Summarization, which condenses long calls into actionable key pointsSentiment Analysis, which helps improve customer interactionsCall Summary Highlights, which allows users to customize high-priority prompts for summariesThese sophisticated analysis tools also integrate into its customers' CRM, enabling seamless updates directly from call summaries into tools like Salesforce, HubSpot, and Zoho.
Finally, the partnership also helped the company prioritize a customer-first product roadmap, facilitating:
Accelerated previous releases like call summary highlights, PII redaction, and enhanced sentiment analysisContinuous updates to meet market demand and customer feedbackFaster adoption of AI into Aloware's product ecosystem, leading to better insights and productivity for customers
Powering long-term product strategy with AI
Aloware has been thrilled with the accurate transcription and AI analysis features it can now offer customers with AssemblyAI's state-of-the-art AI models.
In addition, working with AssemblyAI has gone smoothly, says Sheikhani: "The ongoing support has been strong and AssemblyAI continues to act like real partners, not just vendors." Having AssemblyAI models available on the same AWS architecture leveraged by Alloware allowed for better performance optimization and more efficient resource utilization across both platforms.
For example, Aloware has seen customers like JobNimbus increase lead-to-close rate by 27% with the addition of these AI-powered tools.
What's next for Aloware? The company is exploring predictive analytics for call outcomes and advanced real-time agent assistance using LeMUR, an AssemblyAI service built on AWS Bedrock which helps users leverage LLM capabilities like Anthropic's Claude 3 models and take action on audio data.
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Zoom
AssemblyAI's industry-leading Speech AI models were selected to help advance Zoom’s research and development efforts around speech-to-text by using these models to refine data used to train Zoom’s AI Companion, strengthening Zoom’s ability to deliver high-performance AI features.
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