CallRail sees massive year over year growth for its new pricing SKUs with Conversation Intelligence

Businesses need faster, more efficient ways to extract and leverage insights to optimize their customer acquisition strategy—and platforms like CallRail are using state-of-the-art AI to help these businesses achieve it more easily, quickly, and accurately.

CallRail, a lead intelligence software company, was an early integrator of AI and remains deeply dedicated to investing in new breakthroughs in the field. Today, CallRail’s customers use its AI-powered platform to drive community impact, build meaningful relationships on sales calls, and increase ROI on call tracking.

For example, its conversation intelligence customers realize:

• 50% less time spent reviewing and analyzing calls
• 60% less time spent qualifying leads
• 10% increase in leads from improved marketing

CallRail’s Chief Product Officer, Ryan Johnson, explains that the company has adopted an AI-first approach—where AI acts as a crucial building block when developing new features and products—as the main driver of its product roadmap because of AI’s demonstrated transformative power for its customers.

To achieve this positioning, Johnson and CallRail decided to partner with AssemblyAI, who could provide a secure, scalable AI stack for spoken data. This would help CallRail more quickly build new features and products on top of the latest innovations and deliver them to its customers.

"...we're focused on delivering incredible products that meet the specific needs of our customers. To do that effectively and efficiently, it makes sense for us to partner with experts in AI versus building something from the ground up—which can feel like a space race and act as a barrier to bringing valuable solutions to market in a timely manner," explains Johnson.

AssemblyAI's models are designed using the latest cutting-edge research in AI, with built-in support and security for scalability. The models are accessible through a simple API call, making them easier and faster to build with for teams like Johnson’s.

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CallRail first built a foundation of impressive features on top of AssemblyAI’s speech-to-text and speech understanding models. 

Integrating a production-ready Summarization model enabled CallRail's Engineering Product Design (EPD) teams to focus on designing Conversation Intelligence features that automatically categorize calls, trigger a follow-up action, and more. For example, when a call is run through CallRail’s platform, the platform can auto-score and categorize key sections of the call to help CallRail’s customers more intelligently and efficiently process call data at scale.

Through this initial partnership with AssemblyAI, CallRail improved its call transcription accuracy by up to 23% and doubled the number of customers using its Conversation Intelligence product. For its customers, these changes directly translate into better lead tracking, enhanced relationship building, and cost savings.

CallRail recently released a new AI-first feature, Call Summaries, using AssemblyAI’s Conversational Summarization Model—an AI model purpose-built for multi-person conversations like those that CallRail’s customers process with its platform every day.

Through a single API call, the summarization models synthesize lengthy audio and video data into highly relevant, actionable key points and takeaways. Results can be returned as several summary types, including bullets, bullets verbose, headline, gist, or paragraph.

For CallRail, AI-powered Call Summarization offers a host of new opportunities for its users.

“Businesses that rely on communication with leads to generate revenue have a lot of data to comb through in order to find the insights that help them acquire more customers. The capabilities AI enables us to build help businesses market confidently while saving time and money. It's powerful, almost magical to see it work,” says Johnson.

The Conversational Intelligence leader is also expanding its use of AssemblyAI’s sentiment analysis model, which can automatically detect and label sentiments—positive, neutral, or negative—in speech segments in its customers’ conversational data. Additional Conversation Intelligence features are powered by AssemblyAI’s LeMUR, which lets users leverage LLM capabilities to extract insights from voice data. 

With LeMUR, for example, users can access Anthropic’s Claude LLMs models via AWS bedrock. This partnership allows AssemblyAI to provide the stability and reliability needed to serve high-traffic customers like CallRail.

CallRail’s robust Conversation Intelligence offering is now a fast growing product line. 

‍Want to learn about building AI-powered features from CallRail? Watch for insights on demand.