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Service Resolution Agent

Resolves tier-1 customer service demand end to end across voice and digital.

35–60% of in-scope contacts resolved without a live agent

The problem. Tier-1 contact demand grows with the customer base while service budgets do not, so cost per contact and hold times rise together and specialists spend their day on work that never needed them.

The agent authenticates the customer, understands the intent in their own words, retrieves the account state from your systems of record, and completes the transaction — not just answers a question about it.

It works the same way on voice and in digital channels, holds context across a channel switch, and hands to a human with the full transcript, the actions already taken and the reason for escalation.

Coverage expands intent by intent against a measured containment-quality bar, so the agent only takes on work it demonstrably resolves well.

Before

Every routine status, update or amendment request occupies a live agent for several minutes, and volume spikes are absorbed with overtime and seasonal hiring.

After

Routine demand is resolved in channel within seconds, live agents work the exceptions, and peak volume is absorbed without a hiring cycle.

Reference architecture

Where this agent sits in the stack.

One conversational layer across voice and digital, wired into your CCaaS platform and CRM rather than bolted alongside them.

Customer channelsSystems of record
  1. 01

    Customer channels

    Voice, web chat, mobile app, WhatsApp, SMS and social — one conversation model, channel-specific presentation.

  2. 02

    NLU & dialog orchestration

    Intent, entity and LLM-based understanding, disambiguation, context carry-over and deterministic dialog policy for regulated flows.

  3. 03

    Knowledge & fulfilment

    Grounded retrieval over approved content plus transactional fulfilment through APIs — order status, payments, appointments, account changes.

  4. 04

    Escalation & agent handoff

    Warm transfer with full transcript, intent and authentication state so the customer never repeats themselves.

  5. 05

    CCaaS & systems of record

    Amazon Connect, Genesys Cloud, NICE CXone or Five9 alongside CRM, order management and billing.

Integration surface

  • CCaaS platform (Amazon Connect, Genesys Cloud, NICE CXone or Five9)
  • CRM and case management
  • Order, policy or account system of record
  • Identity and authentication service
  • Knowledge base and policy content

Guardrails & human oversight

  • Refunds, credits and account changes are bounded by policy limits set per intent.
  • Answers are grounded in approved knowledge with citations; the agent says it does not know rather than improvising.
  • Every action outside policy stops at a reviewer queue with the agent's reasoning, evidence and proposed change attached.
  • Vulnerable-customer, complaint and regulatory signals escalate to a live agent immediately.

What has to be true first

  • API access to the systems of record the agent must read and write.
  • A knowledge base with owned, current content for the intents in scope.
  • Contact-reason data good enough to size intents by volume and handle time.
  • An authentication path the agent can call in channel.

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

    Intent sizing from real contact data, containment-quality bar agreed, integration and auth design signed off.

  2. Weeks 3–6 · Build

    Top intents built against sandboxed systems, evaluation set assembled from real transcripts, guardrails and escalation wired.

  3. Weeks 7–10 · Production pilot

    Live traffic on a capped share of contacts, daily quality review, tuning against the baseline.

  4. Quarter 2+ · Scale & run

    Intent coverage expands on a release cadence, with quality, cost and containment reported monthly.

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
Contacts resolved without a live agent35–60% of in-scope intents
Cost per resolved contact25–40% lower
Repeat contact within 24 hours15–30% lower
Average speed to answer at peakHeld flat without seasonal hiring

Model the business case: Contact Center AI ROI calculator →

Production pilot

Two to four intents live on real traffic in one channel, with the evaluation harness, guardrails and reporting handed over.

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

Scale & run

Intent coverage expanded across channels and lines of business, run against containment-quality and cost-per-contact SLAs.

Retained pod · quarterly outcome review · price on request.

Agent specification

The full Service Resolution 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
Get the agent spec

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Delivered with this playbook

Contact center modernization: from IVR to conversational AI

A step-by-step migration model for retiring legacy IVR and moving to conversational AI without breaking CX. Covers platform selection, data readiness, integrations, agent experience, QA and cutover — proven across NICE, Genesys, Amazon Connect, Kore.ai and Five9 estates.

Read the playbook →
Related use cases
Price on request

Get a written estimate for the Service Resolution 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.

solutionService Resolution Agent — routed to this team

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