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Customer Support AI

Albert Ayala, Director of Customer Support, led the creation of Nora, an internal AI chatbot built to make Abnormal’s support team faster and more accurate. Nora works directly in Slack, pulling verified answers from Jira, Salesforce, Confluence, and Highspot so technical support engineers (TSEs) can resolve cases quickly and consistently.

Albert Ayala

October 28, 2025

Customer Support AI Albert Ayala Thumbnail

NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.

Reducing Friction in Knowledge Access

Before Nora, support engineers spent too much time tracking down answers across multiple platforms. That fragmentation slowed down response times and introduced inconsistencies that affected customer experience.

  • Scattered information across Jira, SFDC, Confluence, and Highspot.

  • Teams used different systems, creating communication silos.

  • Quality and speed varied between engineers.

This created friction for both engineers and customers, limiting the team’s ability to scale efficiently.

Albert x Customer Support AI Screengrab 3

Diagram showing how Nora AI gathers answers from Jira, SFDC, Highspot, Confluence, and Support KB to produce a unified response.

Building Nora, the AI assistant

Ayala’s team partnered with the GenAI group to build Nora Technical Support AI, a Slack-based assistant that consolidates knowledge from across Abnormal’s systems. Capabilities include:

  • Searching Jira, Salesforce, Confluence, and Highspot for verified information

  • Generating accurate internal and customer-facing responses

  • Logging each interaction and question in Jira for tracking

  • Connecting with QA and performance monitoring agents for feedback

  • Supporting future onboarding and performance management automations

Nora quickly became an essential teammate in the support Slack channel. Engineers now ask questions and receive consolidated, accurate responses within seconds. This workflow not only speeds up resolutions but also helps new team members learn by example, reducing onboarding time and reinforcing knowledge quality.

Accelerating Response and Quality

Since launch, Nora has improved both engagement and throughput for the Customer Support team. Monthly internal usage jumped from 359 to 983 questions between June and August, and average daily cases handled per engineer increased from 3 to 3.9.

  • Faster, more consistent case responses

  • Improved throughput per engineer

  • Full traceability of every support question via Jira

  • Early integration with Glean QA and performance agents for case audits

  • Foundation for digital customer support at scale

By automating information retrieval and response drafting, Nora gives engineers back time to focus on customer empathy and problem-solving. The next step is expanding Nora’s reach to digital-first customer segments, offering self-service powered by the same intelligence.

Support Excellence at Scale

Early users report that Nora not only saves time but also raises the quality of every answer. Engineers now collaborate around AI-generated responses, refining and sharing best practices directly in Slack. The project reflects a cultural shift toward AI as a partner in operational excellence, setting the stage for onboarding and quality automation built on the same foundation.

Problem

Support engineers searched multiple tools for answers, slowing response times and creating inconsistency.

Solution

Nora, an AI assistant in Slack, retrieves verified information from company systems and drafts responses instantly.

Why it's Cool

Nora gives every engineer fast, consistent access to knowledge, boosting productivity and case quality across the team.

Technologies used:

  • Confluence
  • Highspot
  • Glean
  • Jira
  • Salesforce
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