AI for Customer Service · Free scorer, no sign-up
How much of your support queue could run itself?
AI agents that resolve tickets end-to-end - grounded in your knowledge base, connected to your order and account systems. Score your automation potential in 30 seconds.
Your numbers
Your support reality
Email, chat, and phone combined
Order status, opening hours, password resets, returns, FAQs
Your automation potential
Conservative estimate, based on your numbers
Annual savings potential
£67,392
720 conversations a month handled autonomously
Share of all conversations automatable
48%
Monthly savings potential
£5,616
Adjust the sliders to see your numbers.
Assumptions (conservative)
- 80% of routine conversations can be fully resolved by a well-built AI agent grounded in your knowledge base.
- £0.20 average AI cost per resolved conversation (2026 inference pricing plus tooling).
- Complex and sensitive conversations stay with your team - they're excluded from the savings.
What resolves autonomously - and what stays human
The agent owns
- Order status, delivery, and tracking queries - checked against live systems
- Returns, exchanges, and refunds within your policy limits
- Account changes, password resets, booking amendments
- Product questions answered from your documentation, with sources
- Out-of-hours coverage - nights, weekends, spikes
Your team keeps
- Complaints and anything emotionally charged - escalated with full context
- Refunds and gestures above the agent’s authority threshold
- Edge cases the agent flags as uncertain rather than guessing
- Judgement calls, VIP accounts, and relationship management
Weighing a simpler chatbot instead? Read AI chatbot vs traditional chatbot - or go deeper on the economics with the full ROI calculator. The agent approach is part of our AI agents service.
The AI stack we build on
AI customer service - common questions
How does AI actually help customer service?
Modern AI customer service goes beyond scripted chatbots: an AI agent reads each enquiry, retrieves the answer from your knowledge base and live systems (order status, account details, booking records), resolves the routine ones end-to-end, and hands the complex ones to your team with full context and a suggested reply attached. Industry research puts autonomous resolution at 60-80% of routine queries.
Will it give customers wrong answers?
Not if it's built properly. Production systems ground every answer in your actual documentation and data (retrieval-augmented generation), restrict the AI to approved topics, and escalate anything uncertain to a human. That's the difference between a raw chatbot and an engineered agent - and why implementation quality matters more than model choice.
What's the difference between this and a chatbot?
A chatbot converses; an agent resolves. Answering 'where is my order?' with a tracking link is chatbot territory. Checking the courier API, noticing the parcel is stuck, reshipping it under your policy, and emailing the customer an apology with the new tracking number - that's an agent. Both have their place; the savings live mostly in the second.
How long does it take to deploy?
A first agent handling your top routine query types typically goes live in 2-6 weeks: one week to connect your knowledge base and systems, one to two weeks of supervised running where humans approve its answers, then graduated autonomy. Most teams see measurable deflection within the first month.
Watch it resolve your real tickets
Free 30-minute demo: we build a proof-of-concept on a slice of your actual support history - see the resolution rate before you commit anything.