Custom AI agents, built in weeks, not years.
Most businesses of almost any size have back-office work that is a poor use of their people’s time: re-keying between systems, chasing approvals and payments, checking documents, answering the same questions. An AI agent can take a large share of that work, so your people do the work you hired them for.
The big firms quote months or years and hundreds of thousands of dollars for this. Most of what I build costs thousands or tens of thousands and runs in weeks. Bring me the idea on a free call. I will tell you straight whether an agent can take the workload, and give you a rough plan for building it yourself or having my team build it.
Back-office work your team should not be doing.
The best first agent is rarely the flashy one. It is the back-office work your people repeat day after day, that follows rules most of the time and costs real hours. It is frequent, so the savings add up; it is measurable, so you know it worked; and it is out of the customer’s sight while you learn.
Data entry between systems
Copying orders, contacts and updates from email, portals and spreadsheets into the CRM, the accounting system or the order system.
Invoices and payables
Reading invoices as they arrive, matching them to purchase orders and receipts, and flagging what does not match.
Collections and follow-up
Chasing overdue payments, missing paperwork and pending approvals by email and text, on schedule, in your voice.
Inbox and document intake
Sorting the shared inbox, pulling the data out of forms, contracts and scans, and routing each item to the right person.
Phone calls and scheduling
Answering and placing calls, booking and confirming appointments, and logging what was said.
Reporting and reconciliation
Pulling the weekly numbers from several systems, reconciling them, and writing the summary before the meeting.
What an agent can control.
An AI agent is software that reads, decides and acts toward a goal inside the rules you set. These days an agent can run in the cloud or on a computer in your own office, and work almost any application or website the way a person would. It can receive and make calls, read and send texts and email, and speak and listen in many languages. Within the permissions you grant, that covers most of what a person does at a keyboard or on the phone.
Work any application or website
Log in, search, click, type and fill in forms and move data between systems, the way a person at a keyboard does, including older desktop software with no other way in.
Calls, texts and email, both ways
Answer and place calls, receive and send texts and email, sort, draft and follow up on a schedule, with a person approving whatever should not go out unseen.
Read documents
Invoices, contracts, forms, PDFs and scans, turned into data your systems can use.
Listen and speak, in many languages
Transcribe and summarize calls and meetings and hold a natural conversation, speaking, listening, reading and writing in many languages, including the ones your customers use.
Work your data
Spreadsheets, the CRM, accounting, order and support systems, read and updated within the permissions you set.
Hand off to a person
Route the exceptions, the judgment calls and anything it is unsure about to a named person, with the context attached.
Frontier models and open models, in plain terms.
Each agent has a model doing the thinking. Frontier models, from companies such as Anthropic, Google, OpenAI and xAI, are the strongest reasoners. You reach them over the internet and pay for each piece of work they do.
When we built New Relic AI, I had PhD scientists in Israel building our own models from scratch. Today you can take an open model, give it your documents, and get much of that value in weeks. Open models are published openly, free to download and run. On a server in your own office there is no per-use fee and your data stays in the building. In the cloud they cost a fraction of frontier prices. Think of it as renting versus owning: renting is simple and the landlord maintains it, owning gives you control and a fixed cost, and you look after it.
Good agents often use both: an open model handles the routine volume, and a frontier model takes the hard cases where it earns its cost. That one choice decides much of the running bill, and it is easy to skip. I run two inference servers of my own and work hands on with the models and how they are trained, so the choice is made on what the models can do this quarter, not on a vendor’s brochure.
Someone who has built it, not a shop that bills for it.
A development shop builds what you specify. A large firm brings a partner to the pitch and a team to the work. Here the person who tells you whether to build it has built AI products and run companies.
The boardroom and the server room
I have sat in the boardroom as a CEO, a public-company founder and a Managing Partner, and built AI products as a CEO, a COO and a platform GM. I also run two inference servers of my own. The business call and the technical call get made by the same person, so nothing is lost in translation. The demo is the easy part; getting it into production, keeping the running cost down and making it auditable is the hard part, and that is where an operator matters.
A straight answer first
Some ideas are a subscription tool you can buy today, not a custom agent; some are better fixed with a checklist or a clearer form; and some are not ready for an agent yet. You hear that on the free call, before any money is spent.
Three ways in
Your team builds it from the written plan; we build it together, with your person beside me so they can run and change it afterwards; or my team builds it in weeks, inside your own systems, and hands it over. Whichever way, what is built is yours.
Your data stays yours
Open models can run on your own hardware, so customer and employee data stays in the building. Where a cloud model is the better choice, the agent reads only what its access rule permits.
A number you can check
Each agent starts with a baseline: the hours and the cost of the work before the switch. The result is the share of that work it takes off your people, measured, not estimated.
From idea to a working agent in weeks.
1. A free call about your idea
Forty-five minutes. Tell me the work you want off your team’s plate and the systems it touches. I tell you whether an agent can take it, roughly what it costs to build and run, and how long it takes.
2. A short written plan
If it is viable: the workload, the systems, the model choice, the exceptions and who handles them, the cost to build and to run, and the do-it-yourself path.
3. Build and test in weeks
Your team builds it from the plan, we build it together, or my team builds it, inside your own systems. Before it acts on its own, it is tested on 20 to 30 real cases from last month, including the odd ones, then run beside your team on live work, drafting each item but sending nothing, until you can see which kinds of work it gets right. It goes live on those, with a person approving what should not go out unseen. The 30-day plan walks through it.
4. Run and measure
The agent runs against the baseline with named owners for its work, its access and the result. Exceptions go to a person, each decision is logged, and the result is read in hours and dollars, not in logins.
What agents have taken off people’s plates.
In 1995 I bought a $5,000 server and rented it out for close to $5,000 a month. Three decades on, the hardware math works for agents: one client’s agent runs entirely on open models on a $4,000 server in their own office, so no data left the building. The build was a one-time $5,000 development fee. It took 35 percent of the workload off four employees and saves over $150,000 a year.
My rule is that any process you can model can be mostly automated, with the exceptions routed to people. In customer service, support and claims work, that pattern typically takes 30 to 70 percent of the routine work off a team, and the people keep the cases that need their judgment.
And a CEO with $25M in revenue asked how to use AI without an enterprise budget. We skipped the platform conversation and automated the flows his team re-typed day after day: calls, texts, emails, browser work into systems. A one-time $50,000 investment took $250,000 of annual cost out.
On an enterprise’s AI bill, moving the routine work to open models cut that spend by 80 percent.
A $40 million avionics company cut its legal bills by $400,000 by having AI review and draft its contracts, with its contract reviewer checking the work.
The seats, not the theory
Custom AI agents: the questions people actually ask.
What is a custom AI agent?
Software built for one job in your business: it reads the work as it arrives, decides the steps, uses your systems to carry them out, checks the result and hands the exceptions to a person. Off-the-shelf agents do common jobs inside one app; a custom agent does your job across your systems, by your rules. The plain-English version is in what is an AI agent.
How much does a custom AI agent cost?
Most of what I build costs thousands or tens of thousands to build, and the running cost depends on the model choice; open models on your own server carry no per-use fee. Large firms quote hundreds of thousands and months for a program. You get a rough number on the free call. More on costs, including off-the-shelf tools and AI automation services, in AI agents for business.
How long does it take to build an AI agent?
Weeks for one workload, once the systems it touches and the person who owns the exceptions are named. Programs that span many departments take longer, which is why I start with one workload and let the first win fund the next.
Can my team build it ourselves?
Often, yes. If the job fits a tool you can buy, I will say so. If it needs a custom agent and your team has the skills, the written plan is enough to build from. If you would rather not, my team builds it.
Is my data safe with an AI agent?
It can be safer than the copy-and-paste habits it replaces. Open models can run on your own hardware so data stays in the building; where a cloud model is used, the agent reads only what its access rule permits, a person approves anything that sends, pays or deletes, its attempts and spending are capped, and each decision is logged with what it read.
Will an AI agent replace my people?
It takes the low-value work off them. If someone’s job is simply to repeat steps one through ten, that is not a great investment of what people can do. The back-office tasks an agent handles well tend to be the repetitive ones; the time goes back to customers, judgment and the work you hired them for.
What happens after the agent goes live?
It is measured against the baseline, and the corrections your people make are fed back into its instructions and its test cases. The tests are rerun whenever the model, the instructions or your systems change, because models are updated on the provider’s schedule, not yours.
What if I do not know where AI pays in my business yet?
Then start with the AI Assessment: a fixed-fee look at where AI pays, ranked, with a plan you can run with me, run yourself or shelve. The agent build is for when you already have the workload in mind.
How does custom AI agent development work?
Four steps: a free call about the idea, a short written plan if it is viable, the build in weeks by your team or mine inside your own systems, then running it against a baseline with a person catching the exceptions. AI agent development for one workload is weeks, not a program.
Are you an AI automation consultant or an AI agent developer?
Both, on purpose. As an AI agent consultant, I tell you what is worth automating, whether an agent is the right tool or a subscription or a checklist would do the job, and what it will cost to build and run. As an AI agent developer, my team builds it inside your own systems, we build it together with your person, or your team builds it from the written plan. The free call covers the first part; the build is there when you want it.
Do you work in person?
Mostly by video, and in person when the work calls for it. I am based in Alpharetta, Georgia, so Atlanta-area working sessions are easy.
Bring me the idea.
A free forty-five minute call, no pitch. Tell me the work you want off your team’s plate and the systems it touches. You leave knowing whether an agent can take it, roughly what it costs and how long it takes, and whether to build it yourself or have my team build it.
- Send the note, or book the call if you would rather pick a time.
- Forty-five minutes, on video or across a table in the metro.
- A scope and a number if it makes sense to work together, and a straight no if it does not.
Or reach me directly:
(629) 304-8755
ken@kengavranovic.com
- What is an AI agent?A plain-English guide: how agents work and what they control.
- AI agents for businessWhat they do, what they cost, and a 30-day plan.
- AI consulting and the AI AssessmentWhen you want to know where AI pays before you build.
- AI consulting in AtlantaIn person across the Atlanta metro.
- How PE firms get AI into portfolio companiesThe operator’s playbook for a portfolio.