Six Products, One Support Team, Zero Wasted Searches
Digital.ai, a company grown through acquisitions, faced challenges with its support team navigating six disparate product knowledge bases. They adopted Maven AGI to unify search capabilities internally, enabling engineers to find answers efficiently without context-switching. This successful internal deployment led to a customer-facing AI agent, improving service delivery by allowing customers direct access to a comprehensive, AI-powered knowledge base.
The Business
Digital.ai, a company grown through acquisitions, faced challenges with its support team navigating six disparate product knowledge bases. They adopted Maven AGI to unify search capabilities internally, enabling engineers to find answers efficiently without context-switching. This successful internal deployment led to a customer-facing AI agent, improving service delivery by allowing customers direct access to a comprehensive, AI-powered knowledge base.
Digital.ai · Not specified, but implied large/enterprise due to acquisitions and product portfolio..
Before AI
Digital.ai support engineers had to search six separate knowledge bases for different product lines, leading to wasted time context-switching and searching for answers.
What Changed
Digital.ai implemented Maven AGI first as an internal copilot embedded in Zendesk to unify search across all six product knowledge bases, and later launched a customer-facing AI agent drawing from the same unified knowledge base.
The Result
Support engineers no longer context-switch between six documentation systems, getting relevant answers faster within their existing workflow. Customers can now get direct answers without waiting for a human agent.
Why this matters
AI Unifies Fragmented Knowledge for Enhanced Support and Efficiency
Many businesses, particularly those grown through mergers or acquisitions, struggle with fragmented knowledge bases that hinder efficiency and customer service. Digital.ai's case demonstrates how AI can act as a unifying layer over existing, disparate data sources, making information accessible and actionable for both internal teams and external customers without requiring a complete system overhaul. This approach offers a powerful model for improving operational efficiency and customer satisfaction by leveraging existing information with AI. It highlights how companies can overcome the challenges of data silos, streamlining support processes and empowering customers with self-service options, ultimately leading to better resource allocation and user experience.
Technology Used
Used for:
Source
Results are reported by the identified source/company and have not necessarily been independently verified by AI YAI YAI.
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