A nationwide insurance service provider
The company runs large customer service and outbound sales teams, and regulators impose strict requirements on sales scripts, disclosures and customer data security. Traditional quality control relied on manual sampling of roughly 5% of conversations, leaving most compliance risk below the surface until a regulator raised it.
- Key results
- Conversation quality coverage 100% · Compliance risk incidents down 76% · Policy clause lookup within 5 minutes · Quality review headcount down 60%
More customer cases · +86 132 6589 6872
About 400 agents, serving more than one million customers. Products used: private deployment, ZClaw AIOS enterprise AI operating system, ZClaw Knowledge enterprise knowledge hub
The problem
Manual quality review covered only about 5% of conversations, so misleading sales claims and improper commitments were hard to catch in time. Investment advisors and underwriters spent much of the day searching product clauses, regulatory documents and historical cases. Regulation also required data to stay inside the corporate network, which ruled out public cloud AI services.
Our solution
We completed a private deployment inside their network: the ZClaw AIOS foundation plus a full-coverage AI quality review system that checks every conversation in real time and flags risky scripts automatically. A financial knowledge base consolidates product clauses, regulations and historical cases so advisors and underwriters get cited answers instantly. All data stays inside the network, with every action logged to satisfy audit requirements.
Implementation
- Weeks 1-3
Joint assessment with compliance to define AI boundaries and quality review rules.
- Weeks 4-8
Deploy the private environment and calibrate models against historical conversations.
- Weeks 9-14
Roll out full-coverage review with real-time risk alerts and a review workflow.
- Week 15 on
Launch the financial knowledge base and assistant, then extend to research and underwriting.
Verifiable results
5% sample→100%
baseline→down 76%
30 minutes average→within 5 minutes
baseline→down 60%
* Results describe this project; actual outcomes vary with each company's baseline and scope.
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