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8-Point Improvement in Net Revenue Retention
How a B2B project management platform used AI customer success agents to build predictive health scores, automate at-risk interventions, and improve NRR from 104% to 112%.
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Know which accounts need attention before they tell you. AI customer success agents monitor health, predict churn, automate onboarding, and surface expansion opportunities.
Real outcomes from real builds — not marketing copy.
8-Point Improvement in Net Revenue Retention
How a B2B project management platform used AI customer success agents to build predictive health scores, automate at-risk interventions, and improve NRR from 104% to 112%.
Read deploymentReduction in Churn
How a B2B SaaS company deployed an AI customer success agent to cut churn by 25% and identify 40% more expansion revenue.
Read deploymentIntegrate with your CRM, product analytics, support platform, and billing system. The agent syncs account and usage data.
Define health score weights, churn risk thresholds, onboarding milestones, and expansion triggers for your business.
The agent scores accounts daily, alerts CSMs to risks, triggers onboarding sequences, and surfaces expansion opportunities automatically.
Tell us your workflow — we'll send a free scope and timeline within 48 hours.
Not quite? Take a look at ai support agent — the closest neighbour.
AI customer success agents are proactive — they monitor product usage, engagement patterns, and support history to surface at-risk accounts before they churn, identify expansion opportunities, and automate onboarding sequences. Unlike support agents that react to tickets, CS agents anticipate needs.
Customer success teams typically manage 50–200 accounts per CSM. At that scale, it's impossible to proactively monitor every account. AI agents solve this by tracking product usage data, support ticket patterns, NPS scores, and engagement signals to generate real-time health scores. They alert CSMs when accounts show churn risk, suggest playbooks for re-engagement, automate onboarding check-ins, and flag upsell opportunities based on usage patterns — so CSMs spend time on relationships, not spreadsheets.
Unlike a generic chatbot or manual process, an AI customer success agent runs autonomously and integrates with your existing tools. Gartner projects that by 2026, over 80% of enterprises will have used GenAI APIs or applications.
Pick the path that fits your team and timeline. Most companies start with one and grow into the others.
Wire up a ready platform yourself. Best for hands-on teams comfortable configuring software.
See customer success toolsWe scope, build, and deploy your agent — integrated with your CRM and tools. Best for teams that want it live in days, not months.
See the ROI and cost before you commit — useful for justifying the decision internally.
Customer Churn Cost CalculatorIf you’d rather DIY, these are the tools we’d reach for. Each lets customer success teams and account managers run an AI customer success agent without writing code.
We may earn a commission when you sign up via our links. How we recommend tools
Calculate the true cost of customer churn and how AI customer success agents reduce it by 25%.
Model Salesforce Agentforce ROI — $2/conversation pricing vs Service Cloud alone. Deflection rate, payback period, savings vs hiring.
Compare per-seat vs per-resolution vs usage-based AI agent pricing side by side. Growth-adjusted 12-36 month projection.
Support agents react to inbound tickets. Customer success agents are proactive — they monitor usage and health data to anticipate needs, prevent churn, and drive expansion before the customer reaches out.
At minimum: product usage data and CRM records. For best results, add support ticket history, NPS/CSAT scores, billing data, and engagement metrics (emails opened, meetings attended).
Tell us your workflow and we'll send a free AI build plan for customer success teams and account managers — scope, recommended agents, and a go-live timeline — within 48 hours. No obligation.
Or just email [email protected]