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Back-Office Quality Agent

Checks every transaction for accuracy and compliance instead of a 2% sample.

100% QA coverage instead of a 2–5% sample

The problem. Back-office quality is measured on a sample of a few percent, so errors are found weeks later by the client, coaching targets the wrong behaviours, and remediation costs more than prevention.

The agent reviews every completed transaction against the client's own rules and scoring criteria, scores it, and explains each finding with evidence.

Errors are surfaced while they can still be corrected, and repeat patterns become targeted coaching for named individuals and teams.

Disputed scores go to a human QA lead, whose decision feeds back into calibration.

Before

A 2% sample, lagging error discovery, coaching based on anecdote, and client-found defects.

After

100% review with same-day error correction and coaching driven by real defect patterns.

Reference architecture

Where this agent sits in the stack.

From sampled manual review to scored coverage of every interaction, with calibration and appeal built in.

Quality & coachingSystems of record
  1. 01

    Quality & coaching workspace

    Scorecards, coaching queues, calibration sessions and agent-visible feedback with dispute handling.

  2. 02

    Scoring & evaluation

    LLM scoring against your rubric, confidence thresholds, sampling for human calibration and drift detection per model version.

  3. 03

    Transcription & redaction

    Speech-to-text across languages and channels, with PII/PCI redaction before evaluation and storage.

  4. 04

    Interaction capture

    Recordings, transcripts, screen and metadata drawn from the CCaaS platform and recording estate.

  5. 05

    CCaaS, WFM & systems of record

    Quality outcomes flowing into WFM, performance management and reporting.

Integration surface

  • Workflow and case management
  • Core processing platform
  • QA scoring and coaching tools
  • Workforce management for coaching scheduling

Guardrails & human oversight

  • Scores are advisory input to human QA and coaching, never automated performance action.
  • Every finding cites the rule and the evidence in the transaction.
  • Every action outside policy stops at a reviewer queue with the agent's reasoning, evidence and proposed change attached.
  • Calibration sessions with human QA leads are a standing part of the run model.

What has to be true first

  • Documented scoring criteria per client or process.
  • Access to completed transaction records.
  • A calibrated human QA baseline to measure agreement against.

Security, data & compliance

  • Runs under a dedicated service identity with least-privilege, per-tool scopes — never a shared admin account.
  • Customer and employee data stays inside your tenancy and region; no training on your data by default.
  • PII is redacted before it reaches a model, and prompts, responses and tool calls are retained under your retention policy.
  • Every tool call, input, decision and system write is logged and replayable for audit and model-risk review.
Rollout

How this agent reaches production.

  1. Weeks 1–2 · Scope

    Scoring criteria capture, calibration baseline, client approval.

  2. Weeks 3–6 · Build

    Scoring engine, evidence capture, dispute flow and coaching output.

  3. Weeks 7–10 · Production pilot

    One process line at 100% coverage with weekly calibration.

  4. Quarter 2+ · Scale & run

    Multi-client coverage with defect-trend and coaching-impact reporting.

Measurement plan

What we agree to be measured on.

Ranges drawn from comparable production engagements. Your baseline is agreed before build starts, and the same numbers are reported after go-live.

MetricExpected range
Transaction QA coverage100% versus a 2–5% sample
Time to detect an errorWeeks to same day
Client-found defects40–60% fewer
Agreement with calibrated human QA90%+

Model the business case: BPO Margin ROI calculator →

Production pilot

One process line at full coverage with weekly calibration and a measured defect-detection result.

Fixed-price scope · milestone billing · price on request.

Scale & run

Multi-client, multi-process coverage with coaching integration and monthly quality reporting.

Retained pod · quarterly outcome review · price on request.

Agent specification

The full Back-Office Quality Agent specification, as a PDF.

A multi-page specification your architecture, security and procurement reviewers can read without a call: what the agent does, the architecture, the integration surface, autonomy and guardrails, security posture, rollout plan, measurement plan and engagement shape.

  • Process before and after, with the decision that stays with a human
  • Layered architecture diagram and named integration surface
  • Guardrails, approval gates, escalation and audit trail
  • Security, data handling and compliance posture
  • Phase-by-phase rollout and the measurement plan
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Delivered with this playbook

The Agentic Process Automation Playbook: Replacing Legacy RPA

A migration playbook for enterprises moving from brittle, screen-scraping RPA to agentic AI that reads documents, handles exceptions, makes judgment calls and integrates with existing systems. Includes a retire-vs-replace decision tree, governance controls and the ROI case for finance and operations leaders.

Read the playbook →
Related use cases
Buyer questions

What enterprise buyers ask about this agent.

Short, quotable answers on scope, systems, autonomy, governance, timeline, outcomes and commercial shape.

What does the Back-Office Quality Agent actually do?

Checks every transaction for accuracy and compliance instead of a 2% sample. The agent reviews every completed transaction against the client's own rules and scoring criteria, scores it, and explains each finding with evidence. Errors are surfaced while they can still be corrected, and repeat patterns become targeted coaching for named individuals and teams. Disputed scores go to a human QA lead, whose decision feeds back into calibration.

Which systems does the Back-Office Quality Agent act in?

It works across Workflow / case system, Core processing platform, QA and coaching tools. The named integration surface is Workflow and case management; Core processing platform; QA scoring and coaching tools; Workforce management for coaching scheduling.

Which platforms is the Back-Office Quality Agent built on?

We deliver it on the platforms you already own — AWS Bedrock, Azure OpenAI, NICE CXone. Pronix.ai is a systems integrator, not a software vendor, so the code, prompts and evaluation sets belong to you.

How much autonomy does it have?

Supervised autonomy. Scores are advisory input to human QA and coaching, never automated performance action. Every finding cites the rule and the evidence in the transaction. Every action outside policy stops at a reviewer queue with the agent's reasoning, evidence and proposed change attached. Calibration sessions with human QA leads are a standing part of the run model.

What has to be true before we start?

Documented scoring criteria per client or process. Access to completed transaction records. A calibrated human QA baseline to measure agreement against.

How is it secured and governed?

Runs under a dedicated service identity with least-privilege, per-tool scopes — never a shared admin account. Customer and employee data stays inside your tenancy and region; no training on your data by default. PII is redacted before it reaches a model, and prompts, responses and tool calls are retained under your retention policy. Every tool call, input, decision and system write is logged and replayable for audit and model-risk review.

How long does it take to reach production?

Delivery runs in 4 phases. Weeks 1–2 · Scope: Scoring criteria capture, calibration baseline, client approval. Quarter 2+ · Scale & run: Multi-client coverage with defect-trend and coaching-impact reporting.

What results should we expect?

100% QA coverage instead of a 2–5% sample. Expected ranges from comparable production engagements: Transaction QA coverage 100% versus a 2–5% sample; Time to detect an error Weeks to same day; Client-found defects 40–60% fewer; Agreement with calibrated human QA 90%+. Your baseline is agreed before build starts and reported on the same measures after go-live.

What does an engagement look like?

Production pilot: One process line at full coverage with weekly calibration and a measured defect-detection result. Scale and run: Multi-client, multi-process coverage with coaching integration and monthly quality reporting. Fixed-price pilot with milestone billing, then a retained pod with quarterly outcome reviews.

What does the Back-Office Quality Agent cost?

Price on request. Every agent is scoped to your integration surface, data readiness and compliance posture, so we send a written estimate after a 30-minute scoping call rather than publish a band that would not apply to you.

Next step

Scope the Back-Office Quality Agent against your systems.

A 30-minute working session with the architects who deliver it: your integration surface, the decision that stays with a human, the measurement plan and a written estimate. We reply within one business day.

Price on request

Get a written estimate for the Back-Office Quality Agent.

Tell us the process, the systems it touches and the compliance scope. We come back with a scope, a measurement plan and a written estimate — no published band that would not apply to you.

solutionBack-Office Quality Agent — routed to this team

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