Invoca Signal AI Offering Gets an Upgrade

Invoca has added a range of new capabilities that leverage a combination of generative AI, large language models (LLMs), voice biometrics, and patented machine-learning technologies. All these features aim to help companies drive growth and acquire more customers through actionable insights.

Building on Invoca's flagship offering built in 2017, Signal AI, the features allow companies to unlock insights from phone conversations from which they can supercharge contact center QA and agent coaching.

“Since the introduction of Signal AI in 2017, Invoca has focused on providing innovative, no-code AI solutions that deliver measurable business results – for experts and ordinary business users alike. In this next phase of AI adoption, we’re excited to combine generative AI and LLMs with our market-leading conversation intelligence technology to push the boundaries of what’s possible for marketing, e-commerce, and contact center teams in their quest to drive efficient revenue growth,” said Gregg Johnson, CEO of Invoca. 

The features include the following:

  • Rapid Custom AI Model Creation: Users can create custom algorithms to surface actionable insights from every phone conversation, such as the product a caller is interested in. A semantic search modeled after ChatGPT shows specific moments from relevant calls to review and creates an algorithm to classify similar conversations in the future.
  • AI Smart Alerting: This feature notifies personnel of exceptions in contact center operations. Contact center managers can be alerted right away when call handling or compliance issues arise, and marketing teams can understand fast-moving topics of conversation with customers, such as pricing or competitive shifts and changes in conversion rates and campaign results.
  • ChatGPT Call Summaries: A simple AI-generated call recap that highlights the intent, interest, outcome, and flow of every conversation. This reduces manual post-call work for contact center agents and helps marketers get a deeper understanding of what’s happening when their campaign leads call in.
  • Structured Data Extraction: The feature helps extract zero-party data from unstructured conversations that can help enrich consumer profiles. In cases of automotive dealerships, this data can include the vehicle year, make, and model discussed by a consumer and which is passed into lead management, CRM, and CDP applications for use in automated workflows.
  • Agent Voice ID: This feature uses voice biometric technology to analyze every conversation and identify the agent that handled each call. This is especially valuable for multi-location and franchise businesses where multiple staff members answer calls from one shared phone number.
  • AI Call Review Console: Contact center QA managers can use this feature to speed up the call review and agent coaching process, while teams can create and share call playlists for compliance, auditing, and insight extraction.

Rapid custom AI model creation, AI smart alerting, ChatGPT call summaries, and Agent Voice ID are currently available in beta to select customers. Structured data extraction and AI call review console are expected to be in beta in fall 2023.