AI where it helps. People where it matters.
We use AI to make our teams faster and more consistent — not to replace the person your customer is actually talking to. Automate the repetitive, keep a trained human accountable for the outcome.
Book a 20-minute callWe'll assess fit in 20 minutes and reply within one business day.
Draw the line in the right place
Plenty of providers will tell you AI can handle everything. It can't — and pretending otherwise is how brands end up with customers stuck in a loop. Here's how we split it.
What AI does
Fast, repetitive, and low-consequence when it's wrong.
- Drafting replies for an agent to review
- Summarising long ticket histories
- Surfacing knowledge base articles mid-conversation
- Tagging, routing and prioritising
- Reviewing a far larger QA sample than manual checking allows
- Extracting and classifying data at speed
What people do
Judgement, tone, and anything where being wrong costs you a customer.
- Sending the reply — every one is reviewed by a trained agent
- Handling anything unusual, sensitive or escalated
- Spotting when the automation is confidently wrong
- Fixing the underlying content so it stops recurring
- Verifying extracted data against agreed thresholds
- Owning the outcome your customer actually experiences
Established tools, properly run
Not experiments. These are services we deliver now, using proven tooling and people trained to operate it.
AI-assisted agents
Agents use AI to draft, summarise and retrieve, while remaining the ones who respond. Faster handling without the quality drop that comes from fully automated replies.
Chatbot and automation management
We run the bot you already have — monitoring conversations, spotting where it fails, refining responses and handling every escalation. Most automation underperforms because nobody owns it daily. We own it.
Knowledge base development
Good automation depends on good source material. We write and maintain the documentation your AI draws from, and keep it current as your product changes.
AI-supported quality assurance
Reviewing a far larger share of interactions than manual sampling allows, flagging tone, accuracy and process issues for human review. QA findings that reflect reality rather than a small sample.
Data extraction and processing
AI tooling to speed up document processing, extraction and classification, with human verification against agreed accuracy thresholds. Speed from the tooling, accuracy from the checking.
Workflow automation
Automating repetitive steps in the processes we run for you — routing, tagging, data transfer, routine follow-ups — using the tools already in your stack where possible.
Where we draw the line
Clear about what this is, and isn't
- We deploy and manage established tools — we don't build custom AI models. If you need bespoke model development, we'll point you elsewhere rather than take the work.
- We don't recommend fully autonomous customer-facing AI. Not because it can't work, but because the failure modes damage brands, and we won't put our name to something we can't stand behind.
- Advanced AI and automation consulting is on our roadmap, alongside cybersecurity and IT helpdesk. We'll offer them once we can do them properly.
Being specific about scope is the fastest way for both of us to work out whether this fits — and it's the same clarity you'd get from us on a live account.
Someone has to notice when a bot is confidently wrong.
That's a person's job — and it's part of the service.Automate what's worth automating
Discovery
Current volumes, tooling, and where automation would genuinely help rather than where it sounds impressive.
Design
What gets automated, what stays human, and exactly where the handoff happens.
Training
Academy training, then training on your product, tools and escalation criteria.
Go live
Controlled ramp-up with close monitoring of what the automation gets wrong.
Refine
Tuning content and flows based on real conversations rather than assumptions.
Questions worth asking first
Will AI be talking to our customers?
Only if you want it to, and only for clearly defined interactions. By default our agents use AI to work faster while remaining the ones who respond.
Do you build chatbots from scratch?
We work with the tools in your existing stack rather than building custom systems. If you don't have anything in place, we'll advise on what's appropriate for your volumes.
Will our data be used to train AI models?
Data handling is agreed and documented before work begins, including any restrictions you need on AI processing. Bring your requirements to the call and we'll design around them.
What if we want full automation?
We'll give you an honest view of whether it will work for your use case. Sometimes it does. Where it doesn't, we'd rather say so than sell it and watch it damage your brand.
Does AI mean lower cost?
It can mean better throughput per agent, which affects what a team costs to run. We'd rather discuss that against your actual volumes than quote a headline percentage.
Can you take over an automation that's underperforming?
Yes — that's one of the most common starting points. Usually the issue isn't the tool, it's that nobody owns it day to day or maintains the content behind it.
How do you measure whether it's working?
Containment and deflection rates alongside quality and satisfaction measures. Automation that resolves fewer issues but frustrates more customers isn't a win, and we report it accordingly.
Can this work alongside your other services?
Yes — most clients use it as a layer within customer service, technical support or data processing rather than as a standalone engagement.
Tell us where the time goes
Share where your team spends the most effort, and we'll tell you honestly what's realistically worth automating — and what isn't.