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Case study · BPO · Voice AI

18% lift in right-party contact for a global BPO — agentic outbound collections

A global BPO's largest collections program was missing quota because right-party contact rates had collapsed. pronix.ai deployed a compliance-first agentic outbound stack — smarter dial strategy, natural voice AI for verification, and evidence-grade audit trails — lifting RPC 18% and promise-to-pay 27% inside TCPA and Reg F.

Client
Global BPO, 40,000 seats across 11 countries
Industry
BPO
Platform
Amazon Connect · Salesforce Financial Services Cloud · AWS Bedrock
By pronix.ai CX Engineering8 min readQ1 2026
+18%
Right-party contact
+27%
Promise-to-pay conversion
-45s
Handle time per RPC
0
TCPA / Reg F findings in audit

*Representative outcome; results vary by client, scope and platform configuration.

The challenge

RPC had dropped from 24% to 15% in 18 months, and every dial strategy tweak triggered a compliance review. Agents were spending the first 45 seconds of every connect on verification, and consent capture lived across three systems.

Our approach

Step 01

Compliance-graph dial strategy

Modeled TCPA, Reg F and state-level rules as a decision graph the dialer consulted per attempt — no more one-size-fits-all campaigns.

Step 02

Voice AI for right-party verification

Natural voice agent handled greeting, mini-Miranda and RPC verification — shaving 45 seconds and standardizing script adherence.

Step 03

One consent ledger

Unified consent, DNC and revocation events into a single append-only ledger consumed by both the dialer and the CRM.

Step 04

Agent-assist on connect

Once RPC was confirmed, warm-handed to a human agent with account context, negotiation range and next-best offer pre-loaded.

Step 05

Evidence pack per account

Every attempt produced a regulator-ready evidence bundle — call recording, consent state, script version, model version.

The regulator asked us to prove intent on every dial. We did — in a spreadsheet, in fifteen minutes.

VP Compliance

Stack assumptions

The reference stack behind this program. Assumptions are what pronix.ai brought in on day one — swap-outs are common, and the implementation summary explains where the substitutions cost time or accuracy.

LayerComponentAssumption on day one
Contact centerAmazon Connect (outbound)Predictive + preview dialer with per-attempt policy evaluation; recordings archived to S3 with legal hold.
Compliance graphCustom rules service on AWS Lambda + DynamoDBTCPA, Reg F and state rules modeled as a decision graph; consulted every attempt with sub-50ms latency.
Voice AIAmazon Lex + Polly NeuralGreeting, mini-Miranda and RPC verification only; warm hand-off to human for negotiation.
LLM / summarizationAWS Bedrock (Claude 3.5 Sonnet)Post-call summarization and next-best-offer; guardrails via Bedrock Guardrails on PII and disallowed language.
CRM / account of recordSalesforce Financial Services CloudAccount, consent, promise-to-pay and hardship flags flow both ways; agent desktop unchanged.
Consent ledgerAppend-only store on Amazon Aurora + S3Single source of truth for consent, DNC and revocation; audit exports on demand.
Implementation summary · PDF

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For BPO COOFor Head of CollectionsFor Compliance Officer

Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.

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