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Customer Service Assistant

Business Need​

Empower customer service representatives with an AI assistant that provides instant access to solutions from historical support cases, reducing resolution time and improving consistency in customer interactions.

Solution Overview​

This solution uses Abacus.AI's Custom Chatbot to transform historical case data into an intelligent knowledge base:

Step 1: Ingest Historical Cases

  • Data Source: Historical support case data is ingested from Salesforce using our native connector
  • Data Structure: Cases include customer descriptions, agent responses, resolution steps, case categories, and outcomes
  • Volume: 50,000+ resolved cases spanning 3 years of support history

Step 2: Data Preprocessing

  • Python Feature Group: A custom Python feature group preprocesses raw case text to improve quality
  • Text Cleaning: Removes formatting artifacts, standardizes terminology, and corrects common typos
  • Text Rewriting: Uses an LLM to rewrite messy or unclear case descriptions into clear, concise summaries
  • Metadata Extraction: Automatically tags cases with product areas, issue types, and resolution categories
💡Pro Tip

Preprocessing historical support data significantly improves the custom Chatbots response quality. Raw case notes often contain internal jargon, abbreviations, and formatting issues that confuse retrieval systems.

Step 3: Build Custom Chatbot

A Custom Chatbot is configured with:

  • Knowledge Base: The preprocessed case history serves as the primary knowledge source
  • Response Generation: Synthesizes solutions from multiple relevant cases
  • Citation: Provides links to original Salesforce cases for verification

How It's Used in Practice​

Customer service representatives leverage the Chatbot through the UI provided by Abacus.

During Customer Interactions:

  1. Service representative types a summary into the AI assistant
  2. Chatbot instantly retrieves 3-5 similar historical cases
  3. Service representative reviews suggested solutions and resolution steps and relays back to customer.

Example Queries:

  • "Customer can't log in after password reset"
  • "Billing charge showing twice on account"
  • "Product feature not working on mobile app"
  • "Request for refund on cancelled subscription"

Continuous Improvement:

  • New resolved cases are added to the knowledge base weekly
  • Service representative feedback helps refine retrieval relevance
  • Common unresolved queries identify knowledge gaps

✨Key Outcomes

Key achievements:

⚡ 50% faster resolution time​

Agents find solutions instantly instead of searching manually

🎓 Accelerated agent onboarding​

New agents become more productive productive

Additional Information​