AI & Customer Service Automation
Let the machine take the repeat questions. Your people take the hard ones.
Customers expect an answer at 10pm on a Sunday. Hiring for that is expensive, and most of what comes in at 10pm on a Sunday is the same five questions. That is the part worth automating.
I build the agents and the automations behind them, wired into the systems you already run. Not a chatbot that reads your FAQ back to you: something that can look up the order, make the change, and hand the conversation to a person the moment it's out of its depth. Where that line sits is a decision we make together, in writing.
Key outcomes
Reduce response time
Common questions get answered the moment they're asked, at any hour. First response stops depending on who's awake.
Free up your best people
Your best agents stop answering the same question forty times a day and start working the cases that actually need them.
Scale efficiently
Volume can double without your headcount doubling with it. What the automation can't handle still goes to a person.
Service offerings
I start by reading your actual tickets. Not a sample deck: the real queue, sorted by how often the same thing comes back. The ones at the top are what I automate first. Then I build it, test it against real traffic, and put it live.
Agent deployment
Agents that answer the common questions, triage the rest, and push your bigger accounts to the front of the queue.
Back-office automation
The work a request kicks off: processing a return, updating an account, opening the ticket in your CRM. Done without anyone retyping it.
Sentiment analysis
Read the tone of a live conversation and flag the ones going wrong, so a senior person can step in while it still matters.
Feedback loops
Every question the agent couldn't answer is a gap in your documentation. The system logs them so you can go fill them.
Results
The routine questions stop reaching a person. What's left is the work your team is actually good at. You get faster first responses, a queue that doesn't grow with your customer count, and a running list of what your docs are missing.
See it in practice: sentiment analysis automation for Samsung's Galaxy S20 launch that flagged at-risk customers in the live sales funnel.