AI agents for business
AI agents that do the work, not just talk about it.
An AI agent takes a goal, uses your tools and finishes the job: qualifies the lead, answers the crew, chases the paperwork. I design, build and run custom agents for companies that want the work done, not a demo.
The problem
Most AI agents never earn their keep.
01
Chatbots that only talk
A widget that answers questions but can't book the call, update the CRM or send the file isn't an agent. It's a FAQ with extra steps.
02
Off-the-shelf doesn't fit
Generic agent platforms assume a generic business. Yours has exceptions, edge cases and a way of doing things that took years to get right.
03
Nobody's watching
Agents fail quietly. Without monitoring, you find out a month later that it's been sending the wrong answer to every third customer.
What I build
Agents I build and keep running.
Customer service agents
Answer common questions by chat, email or text, resolve what they can and hand off the rest with the full context attached.
Sales and qualification agents
Screen inbound leads, ask the qualifying questions, and only book the ones worth your team's time.
Operations agents
Track authorizations, deadlines and compliance. Flag problems before they turn into a turned-away customer or a denied claim.
Internal assistants
Your team asks in Slack, Teams or text and gets the answer from your own files and procedures.
Back-office agents
Reports, reconciliation, data entry and document handling. The work that eats hours and needs care, not creativity.
SMS and voice agents
For people in the field or customers who won't open an app. Text is still the most-read channel there is.
Running now
Proof, not promises.
Commercial fire protection contractor
214K files
A field-ops assistant that knows every job file
Read the case →Defense-sector training company
Qualified only
A recruiting pipeline that qualifies before it books
Read the case →Multi-clinic physical therapy group
Every clinic
Authorizations and visit caps that track themselves
Read the case →How it works
Map. Build. Run.
Map
Find where AI pays
One call, then a short audit. I look at where time and money leak: the manual work, the dropped handoffs, the pipeline gaps. You get a ranked list of what to build first and what to leave alone.
Build
Inside the tools you already run
I build into your CRM, your inbox, Slack, your EMR or ERP. Most first systems go live in weeks, not quarters, and you see it working before we talk about the next one.
Run
Owned, watched, improved
Systems break when nobody owns them. I monitor, fix and improve what I build, and add the next system once the first one is paying for itself.
Questions
What people ask before we start.
What's the difference between an AI agent and a chatbot?
A chatbot answers. An agent acts. It can look things up in your systems, make a decision within rules you set, and take the next step: send the text, update the record, book the meeting.
Will AI agents replace my staff?
They replace the repetitive part of your staff's day. In the fire protection build, what got replaced was the stream of calls to the office for spec sheets and job files, not the people answering them.
What happens when an agent gets something wrong?
Anything that matters goes through a human first, every action is logged, and I monitor the agents I build. When something drifts, I fix it before you'd notice.
Do you build custom agents or use a platform?
Whatever fits. Some agents run on platforms you already pay for, some are custom software. I pick based on your business, not on what I'd like to build.
Which AI models do you use?
Mostly Claude, with other models where they're the better tool for the job.
Next step
Which job would you hand an agent first?
Bring the task that eats the most hours. I'll tell you if an agent can own it, and what that would look like.