SaaSAI implementation case study

SaaS – Vertical B2B SaaS ($35M ARR): Onboarding & Expansion Revenue AI System

AI agents for implementation playbooks, health scoring, QBR drafts, and expansion pipeline orchestration.

This case study documents a real client implementation. Identifying details may be withheld where confidentiality applies.

Key takeaway

PrimeAxiom automated the full post-sale lifecycle with AI agents owning telemetry interpretation and revenue motions—not static playbooks.

The engagement

From operational friction to a connected AI system

01 · Context

Business overview

Industry: vertical B2B SaaS. Size: mid-market enterprise mix. Systems: CRM, warehouse, product analytics.

02 · Challenge

Core problem

Manual onboarding plans, late churn detection, ad hoc expansion. Scale broke as ARR grew.

03 · Approach

Solution

PrimeAxiom built a customer success operating system: AI-generated onboarding projects from contract objects, health agents combining product usage and tickets, QBR decks auto-drafted, and expansion triggers to AE workflows.

04 · Impact

Results

Time-to-value −38%; gross churn −27%; expansion pipeline +33%; CSM admin time −41%.

System design

The full automation system

The implementation connects triggers, AI decisions, business rules, human approvals, and downstream actions in one controlled workflow.

Onboarding Factory Agent, Health Agent, QBR Agent, Expansion Router Agent.

Workflow

How the automation runs

1. Closed-won trigger. 2. AI builds milestone plan. 3. Usage + tickets fused into health. 4. Risk alerts to CS/AE. 5. QBR content drafted. 6. Humans strategize. 7. Outcomes refine scoring.

Intelligence layer

AI agents and decision logic

Playbook Agent, Health Agent, Narrative Agent, Expansion Agent.

Under the hood

Technical architecture

Reverse ETL, Postgres, LLM with CRM context, Slack/email actions.

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