Conversational AI

AI Customer Support That Resolves 85% of Tickets Before a Human Sees Them

We build intelligent support automation — AI that understands your products, policies, and customers — that handles the majority of support volume instantly, escalates intelligently, and makes your human agents dramatically more effective.

85%

Average ticket deflection rate

−62%

Support cost reduction

<2s

AI response time (24/7)

Trusted by growth teams at

Definition

What is AI customer support automation?

AI customer support automation is the deployment of large language models trained on company-specific knowledge to handle customer inquiries, troubleshoot issues, process requests, and resolve tickets without human agent involvement — for the majority of support volume. Unlike keyword-based chatbots that follow rigid scripts, AI support systems understand natural language, maintain conversation context, query live customer data, and generate contextually accurate responses. Aroluxa builds AI support systems using Claude, Intercom, Zendesk, and custom knowledge base integrations that achieve 80–90% ticket deflection rates while maintaining high CSAT scores — because AI resolves issues accurately and immediately rather than routing customers through queues.

AI customer supportticket deflectionhelpdesk automationIntercomZendeskClaudeGPT-4support chatbotRAG customer supportCSATfirst contact resolutionn8nknowledge base

The Problem

Why most companies struggle without AI

The same patterns limit every revenue team. Here's what we fix first.

01

Your support team is overwhelmed by repetitive inquiries

The majority of support tickets are repetitive — order status, password resets, billing questions, how-to queries. AI handles these instantly, freeing your agents for complex, high-value interactions that actually require human judgment.

02

Customers wait hours for answers that exist in your docs

Wait times for simple questions damage customer satisfaction. AI support provides accurate, immediate answers at any hour — including nights, weekends, and holidays when your team isn't available.

03

Support costs scale linearly with customer count

Every new customer adds support volume. Without AI deflection, support headcount must grow proportionally. AI support breaks this relationship — handling 10× the volume with the same team.

04

Human agents spend time on admin, not solving problems

Finding customer records, searching documentation, writing responses from scratch — AI handles all of this and drafts the response so agents can focus on nuance, empathy, and complex problem-solving.

Full System Scope

Everything we build, end to end

Every component is custom-built for your stack, ICP, and business model — not templated.

AI Resolution Engine

  • Natural language intent recognition
  • Product & policy knowledge base integration
  • Live customer data querying (CRM/orders)
  • Contextual multi-turn conversation handling

Intelligent Routing

  • Complexity-based escalation logic
  • Sentiment detection & priority routing
  • Agent matching by expertise
  • Warm handoff with full conversation context

Agent Augmentation

  • AI-drafted response suggestions
  • Relevant knowledge article surfacing
  • Customer history summary on ticket open
  • Resolution recommendation engine

Analytics & Optimisation

  • Deflection rate by topic & channel
  • CSAT tracking for AI vs. human
  • Resolution time analytics
  • Knowledge gap identification

Deployment Process

How we build and launch your system

01

Week 1–2

Support Audit & Knowledge Build

Analyse top ticket categories and volumes. Extract all product documentation, policy documents, and FAQ content. Build the AI knowledge base and configure retrieval.

02

Week 2–4

AI Training & Integration

Configure AI support model with company knowledge. Integrate with support platform (Intercom/Zendesk) and live data sources (CRM, order management). Define escalation rules.

03

Week 4–5

Shadow Testing

Run AI in shadow mode — AI generates responses alongside agents for 2 weeks. Measure accuracy, coverage rate, and CSAT on AI-handled tickets. Refine before full launch.

04

Ongoing

Launch & Optimise

Full deployment with continuous monitoring. Monthly analysis of deflection rates, CSAT scores, and knowledge gaps. Knowledge base updates as products evolve.

Live and producing results in 6 weeks.

Book a strategy call

Side-by-Side

AI Support vs. Human-Only Support

Factor
Aroluxa AI Support System
Human-Only Support Team
Response time
<2 seconds, 24/7
Hours during business hours only
Ticket volume capacity
Unlimited, no degradation
Limited by team size
Consistency
Identical quality every response
Variable by agent and day
Cost per ticket
~$0.03–0.12 AI cost
$8–15 average fully-loaded
Scalability
Instant at zero marginal cost
Hiring, training, and ramp time

Built on

ClaudeGPT-4IntercomZendeskn8nSupabasePineconeRetoolSlackStripe

Results

From the field

SaaSSaaS Platform (12,000 customers)

85%

ticket deflection rate within 60 days of launch

AI Customer SupportTicket DeflectionRAGCSAT Improvement

We built an AI support system on Claude with RAG access to their 800-page knowledge base, live CRM data (account status, subscription tier, usage data), and order/billing history via Stripe API. AI handles 85% of tickets autonomously. The remaining 15% are escalated with full context. Average resolution time: 47 hours → 4 minutes. CSAT improved from 3.8 to 4.6 because customers get faster, more accurate answers.

Read full case study

Investment

Build your AI Customer Support system

Fixed-scope builds. Clear deliverables. No hourly billing surprises.

AI Support Starter

$2,500

per month

  • Knowledge base build
  • AI chat integration
  • Basic escalation logic
  • Monthly performance reporting
Get Started
Most Popular

AI Support System

$5,000

per month

  • Everything in Starter
  • Live CRM/data integration
  • Agent augmentation tools
  • CSAT tracking
  • Continuous optimisation
Get Started

AI Support Enterprise

$9,500

per month

  • Everything in System
  • Custom AI model training
  • Multi-channel support (chat, email, SMS)
  • Full analytics dashboard
  • Dedicated support AI engineer
Book a Call

Need a custom enterprise scope? Talk to us

FAQ

Questions, answered.

Everything you need to know about how we build AI Customer Support systems.

Still have questions? Talk to us

We build a RAG (Retrieval Augmented Generation) knowledge base from your documentation — product guides, help articles, policy documents, FAQ content, and past resolved tickets. The AI retrieves relevant content from this knowledge base before generating each response, ensuring answers are grounded in your specific products and policies rather than generic AI knowledge.

AI escalates to a human agent with full context: conversation history, customer record, AI's assessment of the issue, and relevant knowledge articles. Escalation triggers are configurable — by ticket complexity, sentiment, tier of customer, or topic category. Customers never get stuck in an AI loop; escalation is transparent and immediate.

Well-implemented AI support typically achieves CSAT of 4.2–4.7/5 — equal to or better than human agent baselines — because customers value speed and accuracy. The key is resolution quality: AI that gives incorrect answers achieves poor CSAT regardless of speed. Our shadow testing process ensures resolution quality before full deployment.

Yes — we integrate AI with your order management system, billing platform (Stripe, Chargebee), and CRM so the AI can check live order status, subscription details, billing history, and account information. This enables AI to resolve 'where is my order', 'what was I charged for', and 'how do I upgrade' queries autonomously.

Yes — we deploy AI across your existing support channels: live chat on your website, email support (AI drafts responses or handles autonomously), WhatsApp Business, and social DMs. The same AI knowledge base and logic serves all channels with channel-appropriate response formatting.

We build automated knowledge base update pipelines that re-process documentation when it's updated in Notion, Confluence, or your CMS. We also analyse tickets that AI escalated or handled incorrectly to identify knowledge gaps, and update the knowledge base monthly. The AI's knowledge of your product stays current as the product evolves.

Ready to automate?

Let's build your AI Customer Support system

Book a free 30-minute strategy call. Walk away with a system architecture, deployment timeline, and cost estimate. No commitment, no pressure.

Book Intro Call

Free 30-min call · No obligation · System live in 6 weeks