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Automate Customer Service Automation with AI

How to automate customer service automation with AI across 42 industries. Workflow design, AI agents, governance, and the KPIs (first contact resolution, support cost per case, CSAT, and backlog age) we report on weekly. Pick your industry below for a scoped engagement.

Early access: we work with a small first cohort. Engagements are scoped, priced, and shipped end-to-end by our team — not referred to third parties.

Primary outcome

reduce support volume while improving response quality

What we ship

AI service desk, escalation paths, knowledge workflows, and quality dashboards

KPIs we report on

first contact resolution, support cost per case, CSAT, and backlog age

What "automating customer service automation with AI" actually means

Automating customer service automation with AI is not a single product you buy. It is a workflow you redesign around AI as the operating layer. The agent handles the high-volume, high-structure tasks. Humans handle edge cases, exceptions, and trust-sensitive decisions. The system is instrumented to measure first contact resolution, support cost per case, CSAT, and backlog age and improve weekly.

What changes by industry is the systems the agent integrates with, the data it retrieves over, the controls it operates under, and the KPIs it has to defend. The architecture is similar; the integration and the controls are different.

The architecture we use for AI customer service automation

  • Frontier LLM — Claude, GPT-4-class, or Gemini. We benchmark candidates on a labelled test set during Discovery.
  • Retrieval layer over your approved internal sources, with source citations on every output.
  • Tool use for reads and writes against your operational stack (CRM, ERP, ticketing, data warehouse).
  • Reviewer queue for low-confidence outputs. Confidence thresholds set per workflow.
  • Evaluation harness — labelled test set, weekly accuracy reports, regression alerts.
  • Versioned prompts and reviewer-action audit logs for traceability.

Pick your industry

42 industries. Each industry page is a scoped engagement with industry-specific systems, controls, and pricing.

Commerce

Energy

Financial Services

Food and Agriculture

Food and Hospitality

Healthcare

Manufacturing and Industrial

Manufacturing and Mobility

Media

People Operations

Professional Services

Public and Knowledge Services

Public and Social Impact

Public Sector

Real Assets

Supply Chain

Technology

Technology and Communications

Travel and Hospitality

Travel and Mobility

Frequently asked questions

How do you automate customer service automation with AI?+

We map your existing customer service automation workflow, identify high-volume and high-structure tasks, build an AI agent that handles those tasks, and route low-confidence cases to a human reviewer. The build connects to the systems your industry already runs on, runs against a labelled test set, and ships behind a reviewer queue before it sees production traffic. We measure first contact resolution, support cost per case, CSAT, and backlog age from day one and improve weekly.

What is the best AI agent for customer service automation?+

There is no single off-the-shelf "best" agent for customer service automation — the right architecture depends on the systems and data of your industry. We typically combine a frontier LLM (Claude, GPT-4-class, or Gemini) with a retrieval layer over your approved sources, tool-use for your stack, and a reviewer queue. We benchmark candidates against a labelled test set during Discovery and pick the model with the best accuracy/cost ratio.

What does AI customer service automation cost?+

Three phases, billed separately. Discovery sprint: $5k. Build engagement: $18k–$25k. Run retainer: $2k–$3k / mo. ~$28k–$48k typical year 1 (60% take the run option for ~6 months). Pricing varies slightly by industry — see the industry-specific pages below.

How long does it take to deploy AI customer service automation?+

Thin-slice in production in ~6 weeks after Discovery, full Build phase over 6-9 weeks. By day 90, first contact resolution, support cost per case, CSAT, and backlog age is instrumented and you have a baseline against which to expand to adjacent workflows.

Which industries do you build AI customer service automation for?+

All 42 industries listed below. Each industry has its own scoped engagement page with industry-specific systems, controls, and KPIs. Common starting industries include Airlines, Airports, Hotels, Travel Agencies, Banking, and others.

What do we own, and what do you own?+

We own workflow design, prompts, retrieval architecture, evaluation harness, and weekly improvement. You own data access, policy, exception approval, and final commercial decisions. At the end of the engagement, every prompt, eval, and config is handed over — no lock-in.

Start the engagement

Book a discovery call for AI Customer Service Automation

Tell us about your workflow, the systems involved, and the KPI you want to move. We'll send a scoped statement of work within 5 business days.