The AI Meeting Prep Bot is an internal tool built by Haren Bhatia to help GTM reps save time and improve outcomes. It automatically generates role-aware, stage-specific customer briefings, replacing hours of manual research with actionable insights. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
The Customer Success AI Coach is an internal tool built by Tim Davison to help CSMs get faster, personalized coaching. It analyzes Gong call transcripts, maps conversations to key competencies, and sends tailored feedback emails within 30 minutes. The tool saves time, delivers actionable insights, and builds persistent skill profiles for continuous growth. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
The Nora Incident Responder is an AI assistant created by Rishi Kavikondala that automates on-call triage in Slack. It analyzes PagerDuty alerts, gathers metrics, logs, and runbook details, and posts a concise summary with next steps, allowing engineers to focus on fixing issues instead of manual investigation. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
Product managers often spend hours writing PRDs and breaking initiatives into epics and tasks. To fix this, Tushar Amrit built a Jira Orchestrator powered by Nora. It generates structured PRDs, proposes epics, and proactively suggests next steps, saving time and letting humans focus on review instead of repetitive creation. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
The Question Bot series follows Andy Chen’s work to automate prospect Q&A across GTM. Each phase builds precision and trust: structuring Slack questions, grounding answers in code, and deploying cautious AI that delivers verified, human-quality responses without human escalation. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
Tim Davison, an AI Native Product Manager, built the AI-powered Automated Post-Meeting Follow-Up, which drafts accurate, editable emails summarizing meeting actions within minutes. This service saves hours weekly and showcases Abnormal’s rapid, reusable AI innovation. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
The Customer Success Companion gives CSMs a single, trusted workspace for QBR prep, product answers, release insights, and data logic support. It unifies scattered knowledge into fast, accurate guidance so teams spend less time searching and more time driving customer outcomes. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
Tushar Amrit, a software engineer on the Gen AI team, built Nora Salesforce Evidence, a sub-agent that links Nora directly to Salesforce. The goal was simple: help product managers generate clean, complete customer reports in seconds, not hours. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.
Ivan Penev, a senior software engineer, built Post Incident Ops. It's an agent that gathers incident telemetry and drafts Abnormal’s post-mortem template from a raw data dump. The result is faster, complete timelines and clearer action items, reducing fatigue for on-call engineers and accelerating prevention work. NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.