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Commerce.AI
Generative AI platform to automate business conversations

What is Commerce.AI?

Commerce.AI offers a generative AI platform engineered to automate business conversations and analyze unstructured data from multiple sources. It leverages technologies like its proprietary TokenTrim™ to provide cost-effective AI voice agents and data processing. The platform consolidates customer feedback, product information, and market trends from text, voice, and images across numerous languages and sources.

Designed for enterprise scale, Commerce.AI focuses on delivering actionable insights for various business functions, including customer experience, sales, product development, and market strategy. It supports teams like CX, insights, IT, data science, and quality assurance by providing clean, industry-specific data and tools to identify trends, track performance, and make informed decisions. The platform emphasizes security and compliance, adhering to standards like HIPAA, SOC 2, GDPR, and PCI.

Features

  • Generative AI Platform: Automates business conversations and data analysis.
  • TokenTrim™ Technology: Reduces token usage for cost-effective AI voice agents.
  • Multi-Source Data Aggregation: Processes text, voice, and image data from over 170 sources.
  • Multi-Lingual Support: Operates across 119 languages.
  • auto-AGENTS™: AI agents for automating interactions.
  • auto-MATE™: Streamlines tasks for representatives.
  • Voice Survey: Captures direct customer feedback via voice.
  • API & Data Access: Provides access to processed data and insights.
  • Enterprise Security & Compliance: Adheres to HIPAA, SOC 2, GDPR, PCI standards.

Use Cases

  • Automating Customer Service Interactions.
  • Improving Contact Center Efficiency and First-Call Resolution.
  • Analyzing Customer Feedback for Product Development.
  • Generating Market Intelligence and Identifying Trends.
  • Enhancing Sales Playbooks with Customer Language.
  • Empowering Employees with AI Tools.
  • Consolidating CX Tools and Improving ROI.
  • Guiding Company Strategy with Data-Driven Insights.
  • Supporting Data Science Teams with Clean, Structured Data.
  • Monitoring Quality and Identifying Operational Issues.

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