How Aloware saw a 50% usage surge for its AI products with AssemblyAI

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.

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 Voice 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.

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 of AloAi include:

• Automatic Summarization, which condenses long calls into actionable key points
• Sentiment Analysis, which helps improve customer interactions
• Call Summary Highlights, which allows users to customize high-priority prompts for summaries

These 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 analysis
• Continuous updates to meet market demand and customer feedback
• Faster adoption of AI into Aloware's product ecosystem, leading to better insights and productivity for customers

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.